# Getting working directory
import os
import math
import seaborn as sns
sns.set(style='white', rc={'figure.figsize':(10,10)})
os.getcwd()
/Users/piumallick/anaconda3/lib/python3.7/site-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead. import pandas.util.testing as tm
'/Users/piumallick/Documents/2ndSemester/INFSCI2160-DataMining/Python Lab Latest'
# Ignore warnings
import warnings
def fxn():
warnings.warn("deprecated", DeprecationWarning)
with warnings.catch_warnings():
warnings.simplefilter("ignore")
fxn()
# Loading necessary libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import skew
pd.set_option("display.max_rows", None)
pd.set_option("display.max_columns", None)
from sklearn import preprocessing
# Loading the dataset
df = pd.read_csv('PYTHON_LAB_TRAIN.csv')
# Checking sample data
df.head()
| SCHED_SURG_AREA | RACE | ETHNIC_GROUP | PROC_DATE | SCHED_HOSPITAL | CREATE_DT_TM | SCHED_START_DT_TM | SCHED_SURG_PROC_CD | FEMALE | AGE_ON_CONTACT_DATE | BMI | WEIGHT | BP_SYSTOLIC | BP_DIASTOLIC | PULSE | PCPVISIT | METFORMIN_FLAG | OPIOIDS_FLAG | ALPHA_BLOCKERS | CENTRAL_ANTAGONISTS | RENIN | BETA_BLOCKERS | ACE_INHIB | ARB | ALDOSTERONE_BLOCKERS | VASODIALATORS | DIURETICS | CALCIUM_BLOCKERS | STATINS | INSULIN_MEDS | ASPIRIN | WARFARIN | DOACS | PRETERM_17P | MEDROL | PREDNISONE | INHALED_STEROID_WITH_LABA | INHALED_STEROID_WITHOUT_LABA | INHALED_STEROIDS | ASTHMA_BIOLOGICS | SHORT_ACTING_BRONCHO_DIALATORS | TNF_INHIBITORS | IMMUNOMODULATORS | AMINOSALICYLATES | CORTICOSTEROIDS | ARNI | ALLOPURINOL | SEIZURE | MUSCLERELAXANT | DIGOXIN | INOTROPES | ANTI_ARRHYTHMIC | ANTIPLATELET | SULFONYLUREA | GLP_1_AGONIST | THIAZOLIDINEDIONE | SGLT2_INHIBITOR | DPP4_INHIBITOR | ALPHA_GLUCOSIDASE_INHIBITOR | AMYLINOMIMETIC | RAPID_ACTING_INSULIN | SHORT_ACTING_INSULIN | INTERMEDIATE_ACTING_INSULIN | LONG_ACTING_INSULIN | MINOCYCLINE | DOXYCYCLINE | MELATONIN | METHAZOLAMIDE | HYDROXYCHLOROQUINE | ITTC | DMARDS | OBESE_HST | MORBIDOBESE_HST | PH_HST | AFIB_HST | COPD_HST | CHF_HST | DIAB_HST | CAD_HST | OSTEO_HST | HTN_HST | CANCER_HST | LUNG_CANCER_HST | OVARIAN_CANCER_HST | HEAD_NECK_CANCER_HST | BREAST_CANCER_HST | ASTHMA_HST | GERD_HST | FIBROMYALGIA_HST | DEPRESSION_HST | PSORIATIC_ARTHRITIS_HST | RHEUM_ARTHRITIS_HST | LUPUS_HST | VTVF_HST | STROKE_HST | VASCULARDISEASE_HST | LOWBACKPAIN_HST | DVT_HST | PE_HST | HYPOTHYROIDISM_HST | ADRENAL_INSUFFICIENCY_HST | INFERTILITY_HST | CKD_HST | ESRD_HST | OBS_SLEEPAPNEA_HST | CARDIAC_ARREST_HST | HEMO_STROKE_HST | MAJOR_BLEED_HST | MACULAR_DEGEN_HST | ANXIETY_HST | HYPERLIPIDEMIA_HST | HIV_HST | ALZHEIMER_HST | COLORECTAL_CANCER_HST | ENDOMETRIAL_CANCER_HST | GLAUCOMA_HST | HIP_PELVIC_FRACTURE_HST | BENIGN_PROSTATIC_HYPERPLASIA_HST | CIRRHOSIS_HST | CIRRHOSIS_HST_1 | CHOLESTEROL_CLOSEST | HDL_CLOSEST | LDL_CLOSEST | TRIG_CLOSEST | WBC_CLOSEST | HGB_CLOSEST | URIC_ACID_CLOSEST | HCO3_CLOSEST | SODIUM_CLOSEST | CREATININE_CLOSEST | EF_CLOSEST | FEV1_CLOSEST | EOS_CLOSEST | NEUTRO_CLOSEST | MONO_CLOSEST | BASOPHIL_CLOSEST | K_CLOSEST | EGFR_CLOSEST | TSH_CLOSEST | T4_CLOSEST | GLUCOSE_CLOSEST | HBA1C_CLOSEST | ESR_CLOSEST | VITAMIN_D_CLOSEST | MAGNESIUM_CLOSEST | FOLICAC_CLOSEST | VIT_B12_CLOSEST | BNP_CLOSEST | PLATELET_CLOSEST | PA_PRESSURE_CLOSEST | HEMATOCRIT_CLOSEST | ALBUMIN_CLOSEST | PREALBUMIN_CLOSEST | MR_CLOSEST | TR_CLOSEST | MEANPLATELETVOL_CLOSEST | MCH_CLOSEST | RDW_CLOSEST | MCV_CLOSEST | MCHC_CLOSEST | RBC_CLOSEST | LYMPHOCYTE_CLOSEST | CA125_CLOSEST | BILIRUBIN_CLOSEST | ALT_CLOSEST | AST_CLOSEST | CA_CLOSEST | PHOSPHORUS_CLOSEST | URINEPROTEIN_CLOSEST | TOTALPREVIOUSHOSPVISITS | TOTALPREVIOUSEDVISITS | TOTALPREVIOUSPCPVISITS | PREVIOUSSPECIALTYVISIT | PREVIOUSURGENTCAREVISIT | CAV_REC_SEX | CAV_REC_LANG | CAV_REC_AGE | CAV_REC_IPOP | CAV_REC_PRIORITY_CODE | CAV_REC_DISP_CODE | UREA_NITROGEN_MAX_1 | UREA_NITROGEN_MIN_1 | CALCIUM_MAX_1 | CALCIUM_MIN_1 | IRON_MAX_1 | IRON_MIN_1 | GLUCOSE_MAX_1 | GLUCOSE_MIN_1 | HGB_MAX_1 | HGB_MIN_1 | HEMATOCRIT_MAX_1 | HEMATOCRIT_MIN_1 | CHLORIDE_MAX_1 | CHLORIDE_MIN_1 | SODIUM_MAX_1 | SODIUM_MIN_1 | CREATININE_MAX_1 | CREATININE_MIN_1 | CARBON_DIOXIDE_MAX_1 | CARBON_DIOXIDE_MIN_1 | RBC_MAX_1 | RBC_MIN_1 | MCV_MAX_1 | MCV_MIN_1 | MCH_MAX_1 | MCH_MIN_1 | MCHC_MAX_1 | MCHC_MIN_1 | ANION_GAP_MAX_1 | ANION_GAP_MIN_1 | PLATELETS_MAX_1 | PLATELETS_MIN_1 | WBC_MAX_1 | WBC_MIN_1 | MEAN_PLATELET_VOLUME_MAX_1 | MEAN_PLATELET_VOLUME_MIN_1 | EGFR_MAX_1 | EGFR_MIN_1 | RDW_MAX_1 | RDW_MIN_1 | BASOPHILS_MAX_1 | BASOPHILS_MIN_1 | NEUTROPHILS_MAX_1 | NEUTROPHILS_MIN_1 | LYMPHOCYTES_MAX_1 | LYMPHOCYTES_MIN_1 | MONOCYTES_MAX_1 | MONOCYTES_MIN_1 | EOSINOPHILS_MAX_1 | EOSINOPHILS_MIN_1 | MAGNESIUM_MAX_1 | MAGNESIUM_MIN_1 | PHOSPHORUS_MAX_1 | PHOSPHORUS_MIN_1 | INR_MAX_1 | INR_MIN_1 | ALBUMIN_MAX_1 | ALBUMIN_MIN_1 | TOTAL_BILIRUBIN_MAX_1 | TOTAL_BILIRUBIN_MIN_1 | AST_MAX_1 | AST_MIN_1 | ALT_MAX_1 | ALT_MIN_1 | ALKALINE_PHOSPHATASE_MAX_1 | ALKALINE_PHOSPHATASE_MIN_1 | TOTAL_PROTEIN_MAX_1 | TOTAL_PROTEIN_MIN_1 | BUN_CREATININE_RATIO_MAX_1 | ACTIVATED_PTT_MAX_1 | BUN_CREATININE_RATIO_MIN_1 | ACTIVATED_PTT_MIN_1 | TROPONIN_I_MAX_1 | TROPONIN_I_MIN_1 | SPECIFIC_GRAVITY_URINE_MAX_1 | SPECIFIC_GRAVITY_URINE_MIN_1 | PROTEIN_URINE_MAX_1 | PROTEIN_URINE_MIN_1 | PH_URINE_MAX_1 | PH_URINE_MIN_1 | KETONES_URINE_MAX_1 | KETONES_URINE_MIN_1 | URINE_NITRITE_MAX_1 | URINE_NITRITE_MIN_1 | LEUKOCYTE_ESTERASE_MAX_1 | LEUKOCYTE_ESTERASE_MIN_1 | BLOOD_URINE_MAX_1 | BLOOD_URINE_MIN_1 | BILIRUBIN_URINE_MAX_1 | BILIRUBIN_URINE_MIN_1 | UROBILINOGEN_URINE_MAX_1 | UROBILINOGEN_URINE_MIN_1 | WHITE_BLOOD_CELLS_URINE_MAX_1 | WHITE_BLOOD_CELLS_URINE_MIN_1 | RED_BLOOD_CELLS_URINE_MAX_1 | RED_BLOOD_CELLS_URINE_MIN_1 | CALCULATED_OSMOLALITY_MAX_1 | CALCULATED_OSMOLALITY_MIN_1 | DIRECT_BILIRUBIN_MAX_1 | DIRECT_BILIRUBIN_MIN_1 | LACTATE_BLOOD_MAX_1 | LACTATE_BLOOD_MIN_1 | BACTERIA_MAX_1 | BACTERIA_MIN_1 | EPITHELIAL_CELLS_MAX_1 | EPITHELIAL_CELLS_MIN_1 | AG_RATIO_MAX_1 | AG_RATIO_MIN_1 | PCO2_ARTERIAL_MAX_1 | PCO2_ARTERIAL_MIN_1 | ADI_2015 | LOS | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | ALTOR | White | Not Hispanic or Latino | 2/19/2018 0:00 | ALT | 2/13/2018 20:04 | 2/19/2018 7:00 | 3904785 | 0.0 | 73.3 | 28.21 | 3056.0 | 102.0 | 70.0 | 83.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 169.0 | 28.0 | 101.0 | 201.0 | 4.7 | 13.9 | NaN | 23.0 | 137.0 | 1.22 | 76.0 | NaN | 1.5 | 47.0 | 15.6 | 0.6 | 4.2 | 58.0 | NaN | NaN | 91.0 | 5.6 | NaN | NaN | 1.6 | NaN | NaN | NaN | 145.0 | 40.0 | 41.4 | 3.2 | NaN | 2.0 | 2.0 | 7.6 | 30.9 | 16.7 | 91.9 | 33.7 | 4.51 | 35.3 | NaN | 0.6 | 13.0 | 26.0 | 9.0 | NaN | NaN | 1.0 | NaN | NaN | 3.0 | NaN | M | ENG | 72.0 | IP | D | 6 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 68.493519 | 7.660417 |
| 1 | NOROB | White | Not Hispanic or Latino | 2/22/2018 0:00 | NOR | 1/23/2018 9:27 | 2/22/2018 8:00 | 576089753 | 1.0 | 26.1 | 25.61 | 2240.0 | 96.0 | 58.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 6.2 | 11.0 | NaN | NaN | NaN | NaN | NaN | NaN | 0.4 | 74.6 | 6.5 | 0.3 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 177.0 | NaN | 32.1 | NaN | NaN | NaN | NaN | 7.7 | 31.1 | 13.2 | 91.3 | 34.1 | 3.52 | 18.2 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 8.0 | NaN | F | ENG | 23.0 | IP | L | 1 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 75.203533 | 2.575000 |
| 2 | SHYOR | White | Declined | 3/27/2018 0:00 | SHY | 3/6/2018 11:02 | 3/27/2018 7:15 | 3907499 | 1.0 | 19.0 | 37.76 | 3520.0 | NaN | NaN | NaN | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 7.6 | 10.1 | NaN | 28.0 | 139.0 | 0.62 | NaN | NaN | 0.0 | 73.0 | 11.0 | 0.0 | 4.2 | 153.0 | NaN | NaN | 104.0 | NaN | NaN | NaN | 2.3 | NaN | NaN | NaN | 446.0 | NaN | 30.2 | 3.2 | NaN | NaN | NaN | 7.0 | 30.0 | 14.2 | 89.3 | 33.5 | 3.38 | 15.0 | NaN | 0.2 | 26.0 | 14.0 | 9.1 | 3.5 | NaN | 2.0 | NaN | NaN | 2.0 | NaN | F | ENG | 18.0 | IP | F | 6 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 59.740571 | 3.552083 |
| 3 | SHYOR | White | Not Hispanic or Latino | 6/8/2017 0:00 | SHY | 6/6/2017 14:19 | 6/8/2017 13:00 | 3907039 | 0.0 | 74.1 | 29.53 | 3200.0 | NaN | NaN | NaN | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 11.8 | 8.7 | 4.1 | 17.0 | 119.0 | 1.56 | 60.0 | NaN | 5.0 | NaN | 13.0 | 0.0 | 5.2 | 43.0 | 0.426 | NaN | 139.0 | NaN | 11.0 | NaN | 2.6 | 24.8 | 1195.0 | 441.0 | 198.0 | 49.0 | 25.5 | 3.5 | 15.0 | 2.0 | 2.0 | 8.3 | 29.8 | 15.7 | 90.7 | 32.8 | 2.80 | 5.0 | NaN | 0.3 | 15.0 | 13.0 | 8.5 | 4.7 | NaN | 4.0 | NaN | NaN | 8.0 | NaN | M | ENG | 73.0 | IP | F | 6 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 44.761703 | 5.778472 |
| 4 | EASOR | White | Not Hispanic or Latino | 12/20/2017 0:00 | EAS | 12/7/2017 13:52 | 12/20/2017 10:00 | 3907499 | 0.0 | 57.8 | 26.91 | 3398.4 | 120.0 | 60.0 | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 183.0 | 66.0 | 106.0 | 54.0 | 7.9 | 14.3 | NaN | 30.0 | 139.0 | 0.85 | NaN | NaN | 1.0 | 60.0 | 9.0 | 1.0 | 3.7 | 59.0 | NaN | NaN | 86.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 205.0 | NaN | 41.5 | 3.8 | 24.0 | NaN | NaN | 8.1 | 30.8 | 13.2 | 89.5 | 34.4 | 4.64 | 29.0 | NaN | 1.2 | 8.0 | 15.0 | 8.3 | NaN | NaN | NaN | NaN | 3.0 | 4.0 | NaN | M | ENG | 51.0 | EDTR | D | D | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 44.718861 | 1.626389 |
# Checking the statistics of the numerical variables in the dataset
df.describe()
| SCHED_SURG_PROC_CD | FEMALE | AGE_ON_CONTACT_DATE | BMI | WEIGHT | BP_SYSTOLIC | BP_DIASTOLIC | PULSE | PCPVISIT | METFORMIN_FLAG | OPIOIDS_FLAG | ALPHA_BLOCKERS | CENTRAL_ANTAGONISTS | RENIN | BETA_BLOCKERS | ACE_INHIB | ARB | ALDOSTERONE_BLOCKERS | VASODIALATORS | DIURETICS | CALCIUM_BLOCKERS | STATINS | INSULIN_MEDS | ASPIRIN | WARFARIN | DOACS | PRETERM_17P | MEDROL | PREDNISONE | INHALED_STEROID_WITH_LABA | INHALED_STEROID_WITHOUT_LABA | INHALED_STEROIDS | ASTHMA_BIOLOGICS | SHORT_ACTING_BRONCHO_DIALATORS | TNF_INHIBITORS | IMMUNOMODULATORS | AMINOSALICYLATES | CORTICOSTEROIDS | ARNI | ALLOPURINOL | SEIZURE | MUSCLERELAXANT | DIGOXIN | INOTROPES | ANTI_ARRHYTHMIC | ANTIPLATELET | SULFONYLUREA | GLP_1_AGONIST | THIAZOLIDINEDIONE | SGLT2_INHIBITOR | DPP4_INHIBITOR | ALPHA_GLUCOSIDASE_INHIBITOR | AMYLINOMIMETIC | RAPID_ACTING_INSULIN | SHORT_ACTING_INSULIN | INTERMEDIATE_ACTING_INSULIN | LONG_ACTING_INSULIN | MINOCYCLINE | DOXYCYCLINE | MELATONIN | METHAZOLAMIDE | HYDROXYCHLOROQUINE | ITTC | DMARDS | OBESE_HST | MORBIDOBESE_HST | PH_HST | AFIB_HST | COPD_HST | CHF_HST | DIAB_HST | CAD_HST | OSTEO_HST | HTN_HST | CANCER_HST | LUNG_CANCER_HST | OVARIAN_CANCER_HST | HEAD_NECK_CANCER_HST | BREAST_CANCER_HST | ASTHMA_HST | GERD_HST | FIBROMYALGIA_HST | DEPRESSION_HST | PSORIATIC_ARTHRITIS_HST | RHEUM_ARTHRITIS_HST | LUPUS_HST | VTVF_HST | STROKE_HST | VASCULARDISEASE_HST | LOWBACKPAIN_HST | DVT_HST | PE_HST | HYPOTHYROIDISM_HST | ADRENAL_INSUFFICIENCY_HST | INFERTILITY_HST | CKD_HST | ESRD_HST | OBS_SLEEPAPNEA_HST | CARDIAC_ARREST_HST | HEMO_STROKE_HST | MAJOR_BLEED_HST | MACULAR_DEGEN_HST | ANXIETY_HST | HYPERLIPIDEMIA_HST | HIV_HST | ALZHEIMER_HST | COLORECTAL_CANCER_HST | ENDOMETRIAL_CANCER_HST | GLAUCOMA_HST | HIP_PELVIC_FRACTURE_HST | BENIGN_PROSTATIC_HYPERPLASIA_HST | CIRRHOSIS_HST | CIRRHOSIS_HST_1 | CHOLESTEROL_CLOSEST | HDL_CLOSEST | LDL_CLOSEST | TRIG_CLOSEST | WBC_CLOSEST | HGB_CLOSEST | URIC_ACID_CLOSEST | HCO3_CLOSEST | SODIUM_CLOSEST | CREATININE_CLOSEST | EF_CLOSEST | FEV1_CLOSEST | EOS_CLOSEST | NEUTRO_CLOSEST | MONO_CLOSEST | BASOPHIL_CLOSEST | K_CLOSEST | EGFR_CLOSEST | TSH_CLOSEST | T4_CLOSEST | GLUCOSE_CLOSEST | HBA1C_CLOSEST | ESR_CLOSEST | VITAMIN_D_CLOSEST | MAGNESIUM_CLOSEST | FOLICAC_CLOSEST | VIT_B12_CLOSEST | BNP_CLOSEST | PLATELET_CLOSEST | PA_PRESSURE_CLOSEST | HEMATOCRIT_CLOSEST | ALBUMIN_CLOSEST | PREALBUMIN_CLOSEST | MR_CLOSEST | TR_CLOSEST | MEANPLATELETVOL_CLOSEST | MCH_CLOSEST | RDW_CLOSEST | MCV_CLOSEST | MCHC_CLOSEST | RBC_CLOSEST | LYMPHOCYTE_CLOSEST | CA125_CLOSEST | BILIRUBIN_CLOSEST | ALT_CLOSEST | AST_CLOSEST | CA_CLOSEST | PHOSPHORUS_CLOSEST | URINEPROTEIN_CLOSEST | TOTALPREVIOUSHOSPVISITS | TOTALPREVIOUSEDVISITS | TOTALPREVIOUSPCPVISITS | PREVIOUSSPECIALTYVISIT | PREVIOUSURGENTCAREVISIT | CAV_REC_AGE | UREA_NITROGEN_MAX_1 | UREA_NITROGEN_MIN_1 | CALCIUM_MAX_1 | CALCIUM_MIN_1 | IRON_MAX_1 | IRON_MIN_1 | GLUCOSE_MAX_1 | GLUCOSE_MIN_1 | HGB_MAX_1 | HGB_MIN_1 | HEMATOCRIT_MAX_1 | HEMATOCRIT_MIN_1 | CHLORIDE_MAX_1 | CHLORIDE_MIN_1 | SODIUM_MAX_1 | SODIUM_MIN_1 | CREATININE_MAX_1 | CREATININE_MIN_1 | CARBON_DIOXIDE_MAX_1 | CARBON_DIOXIDE_MIN_1 | RBC_MAX_1 | RBC_MIN_1 | MCV_MAX_1 | MCV_MIN_1 | MCH_MAX_1 | MCH_MIN_1 | MCHC_MAX_1 | MCHC_MIN_1 | ANION_GAP_MAX_1 | ANION_GAP_MIN_1 | PLATELETS_MAX_1 | PLATELETS_MIN_1 | WBC_MAX_1 | WBC_MIN_1 | MEAN_PLATELET_VOLUME_MAX_1 | MEAN_PLATELET_VOLUME_MIN_1 | EGFR_MAX_1 | EGFR_MIN_1 | RDW_MAX_1 | RDW_MIN_1 | BASOPHILS_MAX_1 | BASOPHILS_MIN_1 | NEUTROPHILS_MAX_1 | NEUTROPHILS_MIN_1 | LYMPHOCYTES_MAX_1 | LYMPHOCYTES_MIN_1 | MONOCYTES_MAX_1 | MONOCYTES_MIN_1 | EOSINOPHILS_MAX_1 | EOSINOPHILS_MIN_1 | MAGNESIUM_MAX_1 | MAGNESIUM_MIN_1 | PHOSPHORUS_MAX_1 | PHOSPHORUS_MIN_1 | INR_MAX_1 | INR_MIN_1 | ALBUMIN_MAX_1 | ALBUMIN_MIN_1 | TOTAL_BILIRUBIN_MAX_1 | TOTAL_BILIRUBIN_MIN_1 | AST_MAX_1 | AST_MIN_1 | ALT_MAX_1 | ALT_MIN_1 | ALKALINE_PHOSPHATASE_MAX_1 | ALKALINE_PHOSPHATASE_MIN_1 | TOTAL_PROTEIN_MAX_1 | TOTAL_PROTEIN_MIN_1 | BUN_CREATININE_RATIO_MAX_1 | ACTIVATED_PTT_MAX_1 | BUN_CREATININE_RATIO_MIN_1 | ACTIVATED_PTT_MIN_1 | TROPONIN_I_MAX_1 | TROPONIN_I_MIN_1 | SPECIFIC_GRAVITY_URINE_MAX_1 | SPECIFIC_GRAVITY_URINE_MIN_1 | PROTEIN_URINE_MAX_1 | PROTEIN_URINE_MIN_1 | PH_URINE_MAX_1 | PH_URINE_MIN_1 | KETONES_URINE_MAX_1 | KETONES_URINE_MIN_1 | URINE_NITRITE_MAX_1 | URINE_NITRITE_MIN_1 | LEUKOCYTE_ESTERASE_MAX_1 | LEUKOCYTE_ESTERASE_MIN_1 | BLOOD_URINE_MAX_1 | BLOOD_URINE_MIN_1 | BILIRUBIN_URINE_MAX_1 | BILIRUBIN_URINE_MIN_1 | UROBILINOGEN_URINE_MAX_1 | UROBILINOGEN_URINE_MIN_1 | WHITE_BLOOD_CELLS_URINE_MAX_1 | WHITE_BLOOD_CELLS_URINE_MIN_1 | RED_BLOOD_CELLS_URINE_MAX_1 | RED_BLOOD_CELLS_URINE_MIN_1 | CALCULATED_OSMOLALITY_MAX_1 | CALCULATED_OSMOLALITY_MIN_1 | DIRECT_BILIRUBIN_MAX_1 | DIRECT_BILIRUBIN_MIN_1 | LACTATE_BLOOD_MAX_1 | LACTATE_BLOOD_MIN_1 | BACTERIA_MAX_1 | BACTERIA_MIN_1 | EPITHELIAL_CELLS_MAX_1 | EPITHELIAL_CELLS_MIN_1 | AG_RATIO_MAX_1 | AG_RATIO_MIN_1 | PCO2_ARTERIAL_MAX_1 | PCO2_ARTERIAL_MIN_1 | ADI_2015 | LOS | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| count | 8.000000e+04 | 69813.000000 | 69813.000000 | 60741.000000 | 61030.000000 | 58853.000000 | 58797.000000 | 45272.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 69813.000000 | 25639.000000 | 25397.000000 | 25099.000000 | 26500.000000 | 62960.000000 | 63088.000000 | 6339.00000 | 60484.000000 | 60778.000000 | 61215.000000 | 29461.000000 | 5426.000000 | 56432.000000 | 53207.000000 | 56653.000000 | 56359.000000 | 60485.000000 | 58152.000000 | 28202.000000 | 10447.000000 | 61137.000000 | 22821.000000 | 3319.000000 | 12845.000000 | 35349.000000 | 9307.000000 | 14335.000000 | 10701.000000 | 62565.000000 | 14892.000000 | 63070.000000 | 52622.000000 | 12545.000000 | 11712.000000 | 13511.000000 | 61326.000000 | 62624.000000 | 58952.000000 | 62713.000000 | 62625.000000 | 62687.000000 | 56636.000000 | 1266.000000 | 51353.000000 | 51913.000000 | 52164.000000 | 59994.000000 | 27795.000000 | 13038.000000 | 29278.000000 | 22810.000000 | 30399.000000 | 57324.000000 | 4991.000000 | 61105.000000 | 4969.000000 | 4969.000000 | 4875.000000 | 4875.000000 | 1068.000000 | 1068.000000 | 4904.000000 | 4904.000000 | 5056.000000 | 5056.000000 | 5059.000000 | 5059.000000 | 4958.000000 | 4958.000000 | 4959.000000 | 4959.000000 | 4974.000000 | 4974.000000 | 4958.000000 | 4958.000000 | 5013.000000 | 5013.000000 | 5016.000000 | 5016.000000 | 5013.000000 | 5013.000000 | 5013.000000 | 5013.000000 | 4893.000000 | 4893.00000 | 5014.000000 | 5014.000000 | 4998.000000 | 4998.000000 | 4991.000000 | 4991.000000 | 2677.000000 | 2677.000000 | 4574.000000 | 4574.000000 | 4335.000000 | 4335.000000 | 4338.000000 | 4338.000000 | 4322.000000 | 4322.000000 | 4358.000000 | 4358.000000 | 4341.000000 | 4341.000000 | 3524.000000 | 3524.000000 | 2807.000000 | 2807.000000 | 3764.000000 | 3764.000000 | 3852.000000 | 3852.000000 | 3727.000000 | 3727.000000 | 3722.000000 | 3722.000000 | 3722.000000 | 3722.000000 | 3723.000000 | 3723.000000 | 3720.000000 | 3720.000000 | 2217.000000 | 2972.000000 | 2217.000000 | 2972.000000 | 1161.000000 | 1161.000000 | 3325.000000 | 3325.000000 | 2807.000000 | 2807.000000 | 3413.000000 | 3413.000000 | 363.000000 | 363.000000 | 1.0 | 1.0 | 117.000000 | 117.000000 | 134.000000 | 134.000000 | 156.000000 | 156.000000 | 1593.000000 | 1593.000000 | 2166.000000 | 2166.000000 | 2121.000000 | 2121.000000 | 1059.000000 | 1059.000000 | 2166.000000 | 2166.000000 | 0.0 | 0.0 | 6.0 | 6.0 | 1732.000000 | 1732.000000 | 1857.000000 | 1857.000000 | 1179.000000 | 1179.000000 | 74401.000000 | 80000.000000 |
| mean | 1.267181e+08 | 0.581969 | 58.550577 | 30.432342 | 3039.820547 | 128.384178 | 76.327466 | 78.685965 | 0.216435 | 0.116726 | 0.327274 | 0.016358 | 0.000587 | 0.000387 | 0.295819 | 0.210964 | 0.123186 | 0.030453 | 0.019796 | 0.262888 | 0.190423 | 0.366694 | 0.105339 | 0.337430 | 0.057425 | 0.056694 | 0.001318 | 0.033389 | 0.074857 | 0.163265 | 0.134230 | 0.177188 | 0.000673 | 0.180998 | 0.005114 | 0.016473 | 0.009798 | 0.163394 | 0.001547 | 0.033418 | 0.012576 | 0.029307 | 0.013321 | 0.000358 | 0.024036 | 0.068239 | 0.053357 | 0.012433 | 0.005715 | 0.007735 | 0.027273 | 0.000645 | 0.000229 | 0.070159 | 0.010743 | 0.012634 | 0.075659 | 0.002507 | 0.020913 | 0.027416 | 0.000115 | 0.011617 | 0.000559 | 0.036512 | 0.572716 | 0.171587 | 0.008079 | 0.083781 | 0.132927 | 0.079570 | 0.191641 | 0.143383 | 0.062195 | 0.418633 | 0.195093 | 0.015040 | 0.005586 | 0.001289 | 0.033934 | 0.233653 | 0.238494 | 0.027803 | 0.156232 | 0.020612 | 0.025783 | 0.009225 | 0.008537 | 0.077034 | 0.048916 | 0.279318 | 0.034378 | 0.023062 | 0.138126 | 0.024179 | 0.011431 | 0.071247 | 0.027531 | 0.120293 | 0.001404 | 0.005916 | 0.163766 | 0.010041 | 0.163222 | 0.339321 | 0.002349 | 0.015427 | 0.025239 | 0.008007 | 0.028977 | 0.008838 | 0.078295 | 0.020784 | 0.020784 | 168.129635 | 48.905154 | 91.867170 | 144.156630 | 8.672291 | 12.768454 | 5.71759 | 26.225986 | 138.777418 | 1.230113 | 54.700223 | 80.553832 | 2.287022 | 70.200648 | 8.177316 | 0.643683 | 4.101149 | 66.774032 | 3.576160 | 1.176726 | 118.361217 | 6.548360 | 29.535194 | 30.070265 | 1.975396 | 16.901254 | 727.908664 | 488.197511 | 243.355558 | 33.864662 | 38.115252 | 3.644293 | 18.244296 | 1.684725 | 1.683739 | 8.580740 | 29.801747 | 14.827186 | 89.249349 | 33.483293 | 4.401320 | 22.146395 | 173.487362 | 0.662101 | 30.142404 | 29.684840 | 9.138407 | 3.411448 | 0.906351 | 2.526163 | 2.251381 | 4.222343 | 5.345702 | 1.473653 | 56.960871 | 31.066009 | 10.959952 | 9.349333 | 8.049538 | 58.195693 | 38.534644 | 195.594413 | 91.761011 | 13.517544 | 9.950040 | 40.542479 | 29.684938 | 108.868495 | 99.556474 | 141.899355 | 134.165961 | 2.136986 | 0.867407 | 29.497781 | 22.067205 | 4.534183 | 3.365029 | 92.597807 | 86.071212 | 31.204708 | 28.511530 | 34.324636 | 32.473549 | 15.260004 | 8.79438 | 320.430594 | 170.740925 | 14.297559 | 6.322029 | 9.092707 | 7.802925 | 56.806126 | 36.316773 | 16.680695 | 13.965654 | 1.135940 | 0.262053 | 80.215906 | 58.087022 | 27.792226 | 11.207404 | 11.556104 | 5.411358 | 4.533633 | 0.812416 | 2.304058 | 1.650341 | 4.446812 | 2.473637 | 1.725909 | 1.074649 | 3.614772 | 2.824439 | 1.274961 | 0.489268 | 90.799839 | 23.143471 | 90.799839 | 23.143471 | 142.619662 | 75.895246 | 7.353898 | 6.163871 | 24.041132 | 49.272611 | 12.343442 | 29.783748 | 3.733394 | 0.699303 | 1.023009 | 1.014346 | 4.446812 | 2.473637 | 6.501318 | 5.708909 | 14.517906 | 10.977961 | 2.0 | 2.0 | 174.358974 | 40.384615 | 4.841940 | 4.565522 | 0.256410 | 0.185897 | 1.126303 | 0.655242 | 84.462004 | 15.940305 | 96.388967 | 14.173032 | 298.615675 | 285.474032 | 0.714668 | 0.243167 | NaN | NaN | 0.0 | 0.0 | 4.274827 | 1.575058 | 0.956489 | 0.780183 | 47.490670 | 36.324343 | 61.167898 | 4.172534 |
| std | 4.004017e+08 | 0.493239 | 18.155244 | 7.674459 | 854.929967 | 18.050635 | 10.962220 | 14.608239 | 0.411817 | 0.321096 | 0.469222 | 0.126849 | 0.024227 | 0.019662 | 0.456413 | 0.407996 | 0.328653 | 0.171831 | 0.139299 | 0.440205 | 0.392638 | 0.481905 | 0.306991 | 0.472836 | 0.232654 | 0.231259 | 0.036278 | 0.179652 | 0.263163 | 0.369610 | 0.340902 | 0.381830 | 0.025938 | 0.385019 | 0.071327 | 0.127285 | 0.098497 | 0.369727 | 0.039302 | 0.179726 | 0.111438 | 0.168666 | 0.114647 | 0.018920 | 0.153161 | 0.252158 | 0.224746 | 0.110810 | 0.075384 | 0.087608 | 0.162879 | 0.025381 | 0.015137 | 0.255416 | 0.103091 | 0.111688 | 0.264454 | 0.050004 | 0.143094 | 0.163294 | 0.010704 | 0.107154 | 0.023629 | 0.187561 | 0.494688 | 0.377024 | 0.089519 | 0.277061 | 0.339498 | 0.270628 | 0.393595 | 0.350466 | 0.241511 | 0.493338 | 0.396275 | 0.121714 | 0.074533 | 0.035882 | 0.181059 | 0.423157 | 0.426166 | 0.164409 | 0.363077 | 0.142083 | 0.158489 | 0.095602 | 0.092002 | 0.266648 | 0.215695 | 0.448667 | 0.182198 | 0.150100 | 0.345035 | 0.153605 | 0.106302 | 0.257240 | 0.163625 | 0.325306 | 0.037441 | 0.076687 | 0.370066 | 0.099702 | 0.369571 | 0.473482 | 0.048411 | 0.123244 | 0.156851 | 0.089124 | 0.167744 | 0.093594 | 0.268637 | 0.142662 | 0.142662 | 49.566022 | 17.655999 | 39.859074 | 151.831518 | 6.023273 | 2.891663 | 2.29530 | 3.469254 | 52.110247 | 3.363239 | 10.171340 | 25.405989 | 4.712806 | 99.247564 | 10.291154 | 0.815246 | 0.926366 | 587.062491 | 143.184916 | 1.190481 | 53.717548 | 4.391626 | 28.520555 | 17.802718 | 0.429236 | 9.907728 | 542.810658 | 818.005567 | 311.657490 | 64.742666 | 6.001553 | 1.306823 | 8.765387 | 0.742687 | 0.738701 | 4.492555 | 2.656297 | 2.416379 | 36.482576 | 13.646839 | 15.318758 | 39.576597 | 1005.593571 | 1.026320 | 72.288242 | 109.317412 | 0.728784 | 2.004037 | 1.299295 | 2.906964 | 3.253671 | 3.494604 | 5.756465 | 0.986714 | 18.611634 | 25.007432 | 7.370036 | 0.649681 | 0.811520 | 49.757369 | 35.151483 | 126.606407 | 31.160339 | 1.869840 | 2.635568 | 5.450195 | 7.681986 | 4.949213 | 5.506203 | 3.860584 | 4.719319 | 5.316868 | 0.711211 | 3.784207 | 4.299299 | 0.645576 | 0.865980 | 7.126757 | 7.485839 | 2.684648 | 3.056097 | 0.992171 | 1.228935 | 4.008567 | 2.79775 | 148.153603 | 75.765158 | 10.234851 | 2.982428 | 1.408825 | 0.944012 | 21.133715 | 20.972715 | 3.749130 | 1.718625 | 0.987579 | 0.390463 | 11.214114 | 14.134943 | 12.386906 | 8.756639 | 4.764126 | 3.195163 | 3.953264 | 1.373589 | 0.693867 | 0.340963 | 1.610438 | 0.883718 | 1.350755 | 0.207141 | 0.611985 | 0.732565 | 2.215754 | 0.637902 | 281.032139 | 31.189159 | 281.032139 | 31.189159 | 145.730767 | 44.248374 | 0.906815 | 1.047984 | 11.501974 | 36.269423 | 5.906369 | 7.834436 | 12.382099 | 3.733062 | 0.011590 | 0.008460 | 1.610438 | 0.883718 | 0.894287 | 0.715552 | 17.635868 | 14.396499 | NaN | NaN | 209.099608 | 112.899012 | 30.889343 | 30.927423 | 0.663537 | 0.539468 | 1.436956 | 0.920870 | 530.734454 | 85.787278 | 871.617343 | 93.553001 | 10.951715 | 8.301959 | 1.799644 | 0.723216 | NaN | NaN | 0.0 | 0.0 | 7.340965 | 3.670203 | 0.290348 | 0.261699 | 13.987295 | 8.648845 | 17.520428 | 5.889182 |
| min | 3.903406e+06 | 0.000000 | 0.200000 | 10.630000 | 174.960000 | 48.000000 | 2.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 30.000000 | 2.800000 | 0.000000 | 10.000000 | 0.300000 | 1.800000 | 0.20000 | 0.250000 | 3.800000 | 0.090000 | 0.000000 | 9.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 1.800000 | 2.000000 | 0.005000 | 0.100000 | 0.400000 | 1.000000 | 0.080000 | 0.250000 | 0.400000 | 1.000000 | 50.000000 | 0.000000 | 1.000000 | 0.000000 | 4.000000 | 0.300000 | 1.000000 | 1.000000 | 1.000000 | 2.800000 | 12.900000 | 1.800000 | 30.600000 | 18.300000 | 0.890000 | 0.000000 | 1.500000 | 0.000000 | 2.000000 | 3.000000 | 4.000000 | 0.200000 | 0.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 0.000000 | 1.000000 | 0.000000 | 7.100000 | 3.300000 | 6.000000 | 6.000000 | 55.000000 | 13.000000 | 7.500000 | 3.200000 | 21.000000 | 9.700000 | 89.000000 | 65.000000 | 126.000000 | 104.000000 | 0.290000 | 0.120000 | 15.000000 | 2.000000 | 1.530000 | 0.720000 | 60.500000 | 11.600000 | 19.500000 | 16.300000 | 29.800000 | 25.000000 | 2.000000 | 0.00000 | 23.000000 | 3.000000 | 1.200000 | 0.000000 | 5.900000 | 4.900000 | 4.000000 | 0.000000 | 11.900000 | 11.100000 | 0.000000 | 0.000000 | 12.000000 | 0.000000 | 0.700000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.900000 | 0.300000 | 1.400000 | 0.100000 | 0.800000 | 0.800000 | 1.400000 | 0.700000 | 0.100000 | 0.000000 | 3.000000 | 3.000000 | 3.000000 | 3.000000 | 12.000000 | 11.000000 | 2.400000 | 2.400000 | 1.300000 | 19.300000 | 0.000000 | 12.900000 | 0.010000 | 0.010000 | 1.001000 | 1.000000 | 1.400000 | 0.100000 | 5.000000 | 1.006000 | 0.000000 | 0.000000 | 2.0 | 2.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 263.000000 | 242.000000 | 0.000000 | 0.000000 | NaN | NaN | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.200000 | 0.200000 | 0.000000 | 0.000000 | -1.000000 | -226.395139 |
| 25% | 3.904778e+06 | 0.000000 | 46.400000 | 25.090000 | 2448.000000 | 118.000000 | 70.000000 | 68.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 135.000000 | 37.000000 | 64.000000 | 85.000000 | 6.200000 | 11.500000 | 4.20000 | 24.000000 | 137.000000 | 0.740000 | 55.000000 | 64.000000 | 1.000000 | 60.000000 | 6.000000 | 0.200000 | 3.800000 | 59.000000 | 1.007000 | 0.980000 | 91.000000 | 5.500000 | 8.000000 | 17.000000 | 1.800000 | 10.600000 | 371.000000 | 64.000000 | 187.000000 | 24.000000 | 34.600000 | 3.300000 | 11.000000 | 1.000000 | 1.000000 | 7.800000 | 28.500000 | 13.400000 | 85.700000 | 32.900000 | 3.900000 | 14.000000 | 10.625000 | 0.400000 | 14.000000 | 15.000000 | 8.800000 | 2.800000 | 0.000000 | 1.000000 | 1.000000 | 2.000000 | 2.000000 | 1.000000 | 44.000000 | 16.000000 | 6.000000 | 8.900000 | 7.600000 | 26.000000 | 18.000000 | 123.000000 | 76.000000 | 12.300000 | 7.700000 | 37.000000 | 23.000000 | 106.000000 | 97.000000 | 140.000000 | 131.000000 | 0.900000 | 0.550000 | 27.000000 | 20.000000 | 4.100000 | 2.660000 | 88.600000 | 82.300000 | 29.800000 | 27.000000 | 33.700000 | 31.800000 | 13.000000 | 7.00000 | 221.000000 | 120.000000 | 9.500000 | 4.500000 | 8.300000 | 7.100000 | 52.000000 | 20.000000 | 14.000000 | 13.000000 | 0.800000 | 0.000000 | 73.900000 | 50.000000 | 19.000000 | 5.000000 | 8.700000 | 3.000000 | 2.000000 | 0.000000 | 2.000000 | 1.400000 | 3.400000 | 1.800000 | 1.100000 | 1.000000 | 3.200000 | 2.300000 | 0.500000 | 0.280000 | 22.000000 | 11.000000 | 22.000000 | 11.000000 | 76.000000 | 53.000000 | 6.800000 | 5.475000 | 16.000000 | 29.900000 | 8.000000 | 26.000000 | 0.060000 | 0.035000 | 1.016000 | 1.009000 | 3.400000 | 1.800000 | 6.000000 | 5.000000 | 0.000000 | 0.000000 | 2.0 | 2.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.200000 | 0.200000 | 2.000000 | 1.000000 | 3.000000 | 1.000000 | 292.000000 | 281.000000 | 0.100000 | 0.100000 | NaN | NaN | 0.0 | 0.0 | 1.000000 | 0.000000 | 0.800000 | 0.600000 | 39.000000 | 31.000000 | 51.732329 | 1.581250 |
| 50% | 3.907224e+06 | 1.000000 | 61.300000 | 29.260000 | 2936.000000 | 126.000000 | 78.000000 | 77.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 1.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 165.000000 | 46.000000 | 88.000000 | 118.000000 | 7.800000 | 13.000000 | 5.40000 | 26.000000 | 139.000000 | 0.900000 | 55.000000 | 81.000000 | 2.000000 | 68.600000 | 8.000000 | 0.700000 | 4.100000 | 60.000000 | 1.700000 | 1.100000 | 103.000000 | 6.000000 | 19.000000 | 29.000000 | 2.000000 | 15.900000 | 556.000000 | 194.000000 | 231.000000 | 31.000000 | 38.800000 | 3.700000 | 18.000000 | 2.000000 | 2.000000 | 8.400000 | 30.000000 | 14.200000 | 89.400000 | 33.500000 | 4.360000 | 21.000000 | 21.850000 | 0.500000 | 20.000000 | 19.000000 | 9.200000 | 3.300000 | 0.000000 | 2.000000 | 1.000000 | 3.000000 | 4.000000 | 1.000000 | 60.000000 | 22.000000 | 10.000000 | 9.300000 | 8.100000 | 43.500000 | 27.000000 | 154.000000 | 87.000000 | 13.600000 | 9.800000 | 40.800000 | 29.300000 | 108.000000 | 100.000000 | 142.000000 | 135.000000 | 1.120000 | 0.700000 | 29.000000 | 22.700000 | 4.550000 | 3.330000 | 92.200000 | 86.900000 | 31.200000 | 28.900000 | 34.400000 | 32.500000 | 15.000000 | 9.00000 | 287.000000 | 166.000000 | 12.600000 | 5.900000 | 9.000000 | 7.700000 | 57.000000 | 38.000000 | 15.400000 | 13.600000 | 1.000000 | 0.000000 | 82.100000 | 59.000000 | 26.100000 | 9.000000 | 11.000000 | 5.000000 | 3.600000 | 0.100000 | 2.200000 | 1.700000 | 4.100000 | 2.400000 | 1.200000 | 1.000000 | 3.700000 | 2.800000 | 0.700000 | 0.400000 | 35.000000 | 17.000000 | 35.000000 | 17.000000 | 100.000000 | 68.000000 | 7.400000 | 6.200000 | 22.000000 | 34.600000 | 12.000000 | 28.600000 | 0.209000 | 0.060000 | 1.021000 | 1.013000 | 4.100000 | 2.400000 | 6.500000 | 5.500000 | 15.000000 | 15.000000 | 2.0 | 2.0 | 25.000000 | 0.000000 | 0.200000 | 0.000000 | 0.000000 | 0.000000 | 1.000000 | 0.200000 | 6.000000 | 2.000000 | 6.000000 | 2.000000 | 297.000000 | 286.000000 | 0.200000 | 0.100000 | NaN | NaN | 0.0 | 0.0 | 2.000000 | 1.000000 | 0.900000 | 0.800000 | 45.000000 | 36.000000 | 64.225397 | 2.654861 |
| 75% | 5.924212e+07 | 1.000000 | 71.700000 | 34.500000 | 3520.000000 | 139.000000 | 82.000000 | 87.000000 | 0.000000 | 0.000000 | 1.000000 | 0.000000 | 0.000000 | 0.000000 | 1.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 1.000000 | 0.000000 | 1.000000 | 0.000000 | 1.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 1.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 1.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 1.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 1.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 198.000000 | 58.000000 | 115.000000 | 169.000000 | 10.200000 | 14.200000 | 6.80000 | 28.000000 | 141.000000 | 1.120000 | 60.000000 | 98.000000 | 3.000000 | 77.000000 | 9.600000 | 1.000000 | 4.400000 | 60.000000 | 2.770000 | 1.300000 | 126.000000 | 7.000000 | 42.000000 | 40.000000 | 2.200000 | 21.700000 | 921.000000 | 545.000000 | 284.000000 | 40.000000 | 42.300000 | 4.100000 | 24.900000 | 2.000000 | 2.000000 | 9.100000 | 31.400000 | 15.400000 | 93.000000 | 34.100000 | 4.750000 | 28.000000 | 72.950000 | 0.700000 | 30.000000 | 26.000000 | 9.500000 | 3.900000 | 2.000000 | 3.000000 | 2.000000 | 5.000000 | 7.000000 | 2.000000 | 71.000000 | 36.000000 | 14.000000 | 9.700000 | 8.600000 | 71.000000 | 46.000000 | 219.000000 | 101.000000 | 14.800000 | 11.900000 | 44.100000 | 35.200000 | 112.000000 | 103.000000 | 144.000000 | 137.000000 | 1.700000 | 0.920000 | 31.675000 | 25.000000 | 4.950000 | 4.010000 | 96.225000 | 90.700000 | 32.600000 | 30.500000 | 34.900000 | 33.300000 | 17.000000 | 10.60000 | 378.000000 | 212.000000 | 16.900000 | 7.800000 | 9.800000 | 8.400000 | 59.000000 | 51.000000 | 18.200000 | 14.400000 | 1.100000 | 0.400000 | 89.000000 | 67.600000 | 35.000000 | 15.400000 | 13.800000 | 7.400000 | 6.000000 | 1.000000 | 2.500000 | 1.900000 | 5.000000 | 3.000000 | 1.700000 | 1.100000 | 4.000000 | 3.400000 | 1.200000 | 0.500000 | 65.000000 | 25.000000 | 65.000000 | 25.000000 | 147.000000 | 88.000000 | 7.900000 | 6.900000 | 29.000000 | 47.700000 | 15.400000 | 31.900000 | 1.370000 | 0.170000 | 1.026000 | 1.019000 | 5.000000 | 3.000000 | 7.000000 | 6.000000 | 15.000000 | 15.000000 | 2.0 | 2.0 | 500.000000 | 0.000000 | 1.000000 | 0.030000 | 0.000000 | 0.000000 | 1.000000 | 1.000000 | 31.000000 | 5.000000 | 22.000000 | 5.000000 | 303.000000 | 291.000000 | 0.400000 | 0.200000 | NaN | NaN | 0.0 | 0.0 | 5.000000 | 2.000000 | 1.100000 | 1.000000 | 52.000000 | 40.000000 | 72.639728 | 4.642361 |
| max | 3.693088e+09 | 1.000000 | 104.700000 | 89.860000 | 22736.000000 | 249.000000 | 159.000000 | 195.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1654.000000 | 212.000000 | 520.000000 | 10618.000000 | 802.000000 | 312.800000 | 52.50000 | 210.000000 | 12917.000000 | 227.800000 | 91.700000 | 210.000000 | 520.000000 | 8570.000000 | 960.000000 | 80.000000 | 141.000000 | 99999.000000 | 23926.000000 | 113.000000 | 1448.000000 | 606.000000 | 140.000000 | 181.000000 | 9.500000 | 100.000000 | 6000.000000 | 12135.000000 | 75000.000000 | 7747.000000 | 143.300000 | 205.000000 | 62.200000 | 12.000000 | 4.000000 | 436.000000 | 83.700000 | 108.900000 | 9037.000000 | 3413.100000 | 3050.000000 | 3980.000000 | 25515.000000 | 49.800000 | 5836.000000 | 12818.000000 | 94.000000 | 290.000000 | 5.000000 | 188.000000 | 164.000000 | 69.000000 | 273.000000 | 15.000000 | 104.000000 | 201.000000 | 94.000000 | 17.500000 | 11.100000 | 462.000000 | 365.000000 | 2154.000000 | 468.000000 | 21.800000 | 17.800000 | 66.100000 | 57.300000 | 134.000000 | 115.000000 | 171.000000 | 145.000000 | 170.500000 | 10.900000 | 48.000000 | 38.000000 | 8.060000 | 6.760000 | 162.700000 | 134.300000 | 51.500000 | 47.000000 | 43.400000 | 39.800000 | 57.000000 | 23.00000 | 1312.000000 | 740.000000 | 281.500000 | 46.800000 | 63.900000 | 12.300000 | 215.000000 | 127.000000 | 39.700000 | 34.200000 | 34.000000 | 4.300000 | 99.000000 | 97.500000 | 100.000000 | 79.000000 | 59.000000 | 30.000000 | 42.000000 | 18.000000 | 24.700000 | 6.400000 | 16.000000 | 8.000000 | 17.100000 | 4.500000 | 6.000000 | 4.900000 | 35.100000 | 14.800000 | 4952.000000 | 707.000000 | 4952.000000 | 707.000000 | 1949.000000 | 804.000000 | 11.200000 | 9.600000 | 129.000000 | 198.000000 | 40.000000 | 179.000000 | 194.500000 | 64.600000 | 1.102000 | 1.083000 | 16.000000 | 8.000000 | 9.000000 | 9.000000 | 100.000000 | 80.000000 | 2.0 | 2.0 | 500.000000 | 500.000000 | 250.000000 | 250.000000 | 4.000000 | 4.000000 | 12.000000 | 8.000000 | 12949.000000 | 2808.000000 | 27309.000000 | 3257.000000 | 350.000000 | 316.000000 | 26.100000 | 17.840000 | NaN | NaN | 0.0 | 0.0 | 141.000000 | 93.000000 | 3.900000 | 3.100000 | 130.000000 | 84.800000 | 100.000000 | 409.658333 |
# Checking various columns of the dataset
df.columns
Index(['SCHED_SURG_AREA', 'RACE', 'ETHNIC_GROUP', 'PROC_DATE',
'SCHED_HOSPITAL', 'CREATE_DT_TM', 'SCHED_START_DT_TM',
'SCHED_SURG_PROC_CD', 'FEMALE', 'AGE_ON_CONTACT_DATE',
...
'BACTERIA_MAX_1', 'BACTERIA_MIN_1', 'EPITHELIAL_CELLS_MAX_1',
'EPITHELIAL_CELLS_MIN_1', 'AG_RATIO_MAX_1', 'AG_RATIO_MIN_1',
'PCO2_ARTERIAL_MAX_1', 'PCO2_ARTERIAL_MIN_1', 'ADI_2015', 'LOS'],
dtype='object', length=292)
# Checking the datatypes of the columns
df.dtypes
SCHED_SURG_AREA object RACE object ETHNIC_GROUP object PROC_DATE object SCHED_HOSPITAL object CREATE_DT_TM object SCHED_START_DT_TM object SCHED_SURG_PROC_CD int64 FEMALE float64 AGE_ON_CONTACT_DATE float64 BMI float64 WEIGHT float64 BP_SYSTOLIC float64 BP_DIASTOLIC float64 PULSE float64 PCPVISIT float64 METFORMIN_FLAG float64 OPIOIDS_FLAG float64 ALPHA_BLOCKERS float64 CENTRAL_ANTAGONISTS float64 RENIN float64 BETA_BLOCKERS float64 ACE_INHIB float64 ARB float64 ALDOSTERONE_BLOCKERS float64 VASODIALATORS float64 DIURETICS float64 CALCIUM_BLOCKERS float64 STATINS float64 INSULIN_MEDS float64 ASPIRIN float64 WARFARIN float64 DOACS float64 PRETERM_17P float64 MEDROL float64 PREDNISONE float64 INHALED_STEROID_WITH_LABA float64 INHALED_STEROID_WITHOUT_LABA float64 INHALED_STEROIDS float64 ASTHMA_BIOLOGICS float64 SHORT_ACTING_BRONCHO_DIALATORS float64 TNF_INHIBITORS float64 IMMUNOMODULATORS float64 AMINOSALICYLATES float64 CORTICOSTEROIDS float64 ARNI float64 ALLOPURINOL float64 SEIZURE float64 MUSCLERELAXANT float64 DIGOXIN float64 INOTROPES float64 ANTI_ARRHYTHMIC float64 ANTIPLATELET float64 SULFONYLUREA float64 GLP_1_AGONIST float64 THIAZOLIDINEDIONE float64 SGLT2_INHIBITOR float64 DPP4_INHIBITOR float64 ALPHA_GLUCOSIDASE_INHIBITOR float64 AMYLINOMIMETIC float64 RAPID_ACTING_INSULIN float64 SHORT_ACTING_INSULIN float64 INTERMEDIATE_ACTING_INSULIN float64 LONG_ACTING_INSULIN float64 MINOCYCLINE float64 DOXYCYCLINE float64 MELATONIN float64 METHAZOLAMIDE float64 HYDROXYCHLOROQUINE float64 ITTC float64 DMARDS float64 OBESE_HST float64 MORBIDOBESE_HST float64 PH_HST float64 AFIB_HST float64 COPD_HST float64 CHF_HST float64 DIAB_HST float64 CAD_HST float64 OSTEO_HST float64 HTN_HST float64 CANCER_HST float64 LUNG_CANCER_HST float64 OVARIAN_CANCER_HST float64 HEAD_NECK_CANCER_HST float64 BREAST_CANCER_HST float64 ASTHMA_HST float64 GERD_HST float64 FIBROMYALGIA_HST float64 DEPRESSION_HST float64 PSORIATIC_ARTHRITIS_HST float64 RHEUM_ARTHRITIS_HST float64 LUPUS_HST float64 VTVF_HST float64 STROKE_HST float64 VASCULARDISEASE_HST float64 LOWBACKPAIN_HST float64 DVT_HST float64 PE_HST float64 HYPOTHYROIDISM_HST float64 ADRENAL_INSUFFICIENCY_HST float64 INFERTILITY_HST float64 CKD_HST float64 ESRD_HST float64 OBS_SLEEPAPNEA_HST float64 CARDIAC_ARREST_HST float64 HEMO_STROKE_HST float64 MAJOR_BLEED_HST float64 MACULAR_DEGEN_HST float64 ANXIETY_HST float64 HYPERLIPIDEMIA_HST float64 HIV_HST float64 ALZHEIMER_HST float64 COLORECTAL_CANCER_HST float64 ENDOMETRIAL_CANCER_HST float64 GLAUCOMA_HST float64 HIP_PELVIC_FRACTURE_HST float64 BENIGN_PROSTATIC_HYPERPLASIA_HST float64 CIRRHOSIS_HST float64 CIRRHOSIS_HST_1 float64 CHOLESTEROL_CLOSEST float64 HDL_CLOSEST float64 LDL_CLOSEST float64 TRIG_CLOSEST float64 WBC_CLOSEST float64 HGB_CLOSEST float64 URIC_ACID_CLOSEST float64 HCO3_CLOSEST float64 SODIUM_CLOSEST float64 CREATININE_CLOSEST float64 EF_CLOSEST float64 FEV1_CLOSEST float64 EOS_CLOSEST float64 NEUTRO_CLOSEST float64 MONO_CLOSEST float64 BASOPHIL_CLOSEST float64 K_CLOSEST float64 EGFR_CLOSEST float64 TSH_CLOSEST float64 T4_CLOSEST float64 GLUCOSE_CLOSEST float64 HBA1C_CLOSEST float64 ESR_CLOSEST float64 VITAMIN_D_CLOSEST float64 MAGNESIUM_CLOSEST float64 FOLICAC_CLOSEST float64 VIT_B12_CLOSEST float64 BNP_CLOSEST float64 PLATELET_CLOSEST float64 PA_PRESSURE_CLOSEST float64 HEMATOCRIT_CLOSEST float64 ALBUMIN_CLOSEST float64 PREALBUMIN_CLOSEST float64 MR_CLOSEST float64 TR_CLOSEST float64 MEANPLATELETVOL_CLOSEST float64 MCH_CLOSEST float64 RDW_CLOSEST float64 MCV_CLOSEST float64 MCHC_CLOSEST float64 RBC_CLOSEST float64 LYMPHOCYTE_CLOSEST float64 CA125_CLOSEST float64 BILIRUBIN_CLOSEST float64 ALT_CLOSEST float64 AST_CLOSEST float64 CA_CLOSEST float64 PHOSPHORUS_CLOSEST float64 URINEPROTEIN_CLOSEST float64 TOTALPREVIOUSHOSPVISITS float64 TOTALPREVIOUSEDVISITS float64 TOTALPREVIOUSPCPVISITS float64 PREVIOUSSPECIALTYVISIT float64 PREVIOUSURGENTCAREVISIT float64 CAV_REC_SEX object CAV_REC_LANG object CAV_REC_AGE float64 CAV_REC_IPOP object CAV_REC_PRIORITY_CODE object CAV_REC_DISP_CODE object UREA_NITROGEN_MAX_1 float64 UREA_NITROGEN_MIN_1 float64 CALCIUM_MAX_1 float64 CALCIUM_MIN_1 float64 IRON_MAX_1 float64 IRON_MIN_1 float64 GLUCOSE_MAX_1 float64 GLUCOSE_MIN_1 float64 HGB_MAX_1 float64 HGB_MIN_1 float64 HEMATOCRIT_MAX_1 float64 HEMATOCRIT_MIN_1 float64 CHLORIDE_MAX_1 float64 CHLORIDE_MIN_1 float64 SODIUM_MAX_1 float64 SODIUM_MIN_1 float64 CREATININE_MAX_1 float64 CREATININE_MIN_1 float64 CARBON_DIOXIDE_MAX_1 float64 CARBON_DIOXIDE_MIN_1 float64 RBC_MAX_1 float64 RBC_MIN_1 float64 MCV_MAX_1 float64 MCV_MIN_1 float64 MCH_MAX_1 float64 MCH_MIN_1 float64 MCHC_MAX_1 float64 MCHC_MIN_1 float64 ANION_GAP_MAX_1 float64 ANION_GAP_MIN_1 float64 PLATELETS_MAX_1 float64 PLATELETS_MIN_1 float64 WBC_MAX_1 float64 WBC_MIN_1 float64 MEAN_PLATELET_VOLUME_MAX_1 float64 MEAN_PLATELET_VOLUME_MIN_1 float64 EGFR_MAX_1 float64 EGFR_MIN_1 float64 RDW_MAX_1 float64 RDW_MIN_1 float64 BASOPHILS_MAX_1 float64 BASOPHILS_MIN_1 float64 NEUTROPHILS_MAX_1 float64 NEUTROPHILS_MIN_1 float64 LYMPHOCYTES_MAX_1 float64 LYMPHOCYTES_MIN_1 float64 MONOCYTES_MAX_1 float64 MONOCYTES_MIN_1 float64 EOSINOPHILS_MAX_1 float64 EOSINOPHILS_MIN_1 float64 MAGNESIUM_MAX_1 float64 MAGNESIUM_MIN_1 float64 PHOSPHORUS_MAX_1 float64 PHOSPHORUS_MIN_1 float64 INR_MAX_1 float64 INR_MIN_1 float64 ALBUMIN_MAX_1 float64 ALBUMIN_MIN_1 float64 TOTAL_BILIRUBIN_MAX_1 float64 TOTAL_BILIRUBIN_MIN_1 float64 AST_MAX_1 float64 AST_MIN_1 float64 ALT_MAX_1 float64 ALT_MIN_1 float64 ALKALINE_PHOSPHATASE_MAX_1 float64 ALKALINE_PHOSPHATASE_MIN_1 float64 TOTAL_PROTEIN_MAX_1 float64 TOTAL_PROTEIN_MIN_1 float64 BUN_CREATININE_RATIO_MAX_1 float64 ACTIVATED_PTT_MAX_1 float64 BUN_CREATININE_RATIO_MIN_1 float64 ACTIVATED_PTT_MIN_1 float64 TROPONIN_I_MAX_1 float64 TROPONIN_I_MIN_1 float64 SPECIFIC_GRAVITY_URINE_MAX_1 float64 SPECIFIC_GRAVITY_URINE_MIN_1 float64 PROTEIN_URINE_MAX_1 float64 PROTEIN_URINE_MIN_1 float64 PH_URINE_MAX_1 float64 PH_URINE_MIN_1 float64 KETONES_URINE_MAX_1 float64 KETONES_URINE_MIN_1 float64 URINE_NITRITE_MAX_1 float64 URINE_NITRITE_MIN_1 float64 LEUKOCYTE_ESTERASE_MAX_1 float64 LEUKOCYTE_ESTERASE_MIN_1 float64 BLOOD_URINE_MAX_1 float64 BLOOD_URINE_MIN_1 float64 BILIRUBIN_URINE_MAX_1 float64 BILIRUBIN_URINE_MIN_1 float64 UROBILINOGEN_URINE_MAX_1 float64 UROBILINOGEN_URINE_MIN_1 float64 WHITE_BLOOD_CELLS_URINE_MAX_1 float64 WHITE_BLOOD_CELLS_URINE_MIN_1 float64 RED_BLOOD_CELLS_URINE_MAX_1 float64 RED_BLOOD_CELLS_URINE_MIN_1 float64 CALCULATED_OSMOLALITY_MAX_1 float64 CALCULATED_OSMOLALITY_MIN_1 float64 DIRECT_BILIRUBIN_MAX_1 float64 DIRECT_BILIRUBIN_MIN_1 float64 LACTATE_BLOOD_MAX_1 float64 LACTATE_BLOOD_MIN_1 float64 BACTERIA_MAX_1 float64 BACTERIA_MIN_1 float64 EPITHELIAL_CELLS_MAX_1 float64 EPITHELIAL_CELLS_MIN_1 float64 AG_RATIO_MAX_1 float64 AG_RATIO_MIN_1 float64 PCO2_ARTERIAL_MAX_1 float64 PCO2_ARTERIAL_MIN_1 float64 ADI_2015 float64 LOS float64 dtype: object
# Making a copy of the dataset
train_df = df.copy()
# Importing LabelEncoder (for transforming non-numerical variables to numeric variables)
le = preprocessing.LabelEncoder()
# Label Encoding SCHED_SURG_AREA
le.fit(train_df['SCHED_SURG_AREA'])
train_df['SCHED_SURG_AREA'] = le.transform(train_df['SCHED_SURG_AREA'])
# Label Encoding RACE
train_df['RACE'] = le.fit_transform(train_df['RACE'].apply(str))
# Label Encoding ETHNIC_GROUP
train_df['ETHNIC_GROUP'] = le.fit_transform(train_df['ETHNIC_GROUP'].apply(str))
# Label Encoding SCHED_HOSPITAL
train_df['SCHED_HOSPITAL'] = le.fit_transform(train_df['SCHED_HOSPITAL'].apply(str))
# Label Encoding SCHED_SURG_PROC_CD
train_df['SCHED_SURG_PROC_CD'] = le.fit_transform(train_df['SCHED_SURG_PROC_CD'].apply(str))
# Label Encoding FEMALE
train_df['FEMALE'] = le.fit_transform(train_df['FEMALE'].apply(str))
# Label Encoding CAV_REC_SEX
train_df['CAV_REC_SEX'] = le.fit_transform(train_df['CAV_REC_SEX'].apply(str))
# Label Encoding CAV_REC_LANG
train_df['CAV_REC_LANG'] = le.fit_transform(train_df['CAV_REC_LANG'].apply(str))
# Label Encoding CAV_REC_IPOP
train_df['CAV_REC_IPOP'] = le.fit_transform(train_df['CAV_REC_IPOP'].apply(str))
# Label Encoding CAV_REC_PRIORITY_CODE
train_df['CAV_REC_PRIORITY_CODE'] = le.fit_transform(train_df['CAV_REC_PRIORITY_CODE'].apply(str))
# Label Encoding CAV_REC_DISP_CODE
train_df['CAV_REC_DISP_CODE'] = le.fit_transform(train_df['CAV_REC_DISP_CODE'].apply(str))
# Label Encoding LOS_Binary
train_df['LOS_Binary'] = train_df.apply(lambda x: 1 if (x['LOS'] > 5) else 0,axis=1)
# Checking sample values (after Label Encoding)
train_df.head()
| SCHED_SURG_AREA | RACE | ETHNIC_GROUP | PROC_DATE | SCHED_HOSPITAL | CREATE_DT_TM | SCHED_START_DT_TM | SCHED_SURG_PROC_CD | FEMALE | AGE_ON_CONTACT_DATE | BMI | WEIGHT | BP_SYSTOLIC | BP_DIASTOLIC | PULSE | PCPVISIT | METFORMIN_FLAG | OPIOIDS_FLAG | ALPHA_BLOCKERS | CENTRAL_ANTAGONISTS | RENIN | BETA_BLOCKERS | ACE_INHIB | ARB | ALDOSTERONE_BLOCKERS | VASODIALATORS | DIURETICS | CALCIUM_BLOCKERS | STATINS | INSULIN_MEDS | ASPIRIN | WARFARIN | DOACS | PRETERM_17P | MEDROL | PREDNISONE | INHALED_STEROID_WITH_LABA | INHALED_STEROID_WITHOUT_LABA | INHALED_STEROIDS | ASTHMA_BIOLOGICS | SHORT_ACTING_BRONCHO_DIALATORS | TNF_INHIBITORS | IMMUNOMODULATORS | AMINOSALICYLATES | CORTICOSTEROIDS | ARNI | ALLOPURINOL | SEIZURE | MUSCLERELAXANT | DIGOXIN | INOTROPES | ANTI_ARRHYTHMIC | ANTIPLATELET | SULFONYLUREA | GLP_1_AGONIST | THIAZOLIDINEDIONE | SGLT2_INHIBITOR | DPP4_INHIBITOR | ALPHA_GLUCOSIDASE_INHIBITOR | AMYLINOMIMETIC | RAPID_ACTING_INSULIN | SHORT_ACTING_INSULIN | INTERMEDIATE_ACTING_INSULIN | LONG_ACTING_INSULIN | MINOCYCLINE | DOXYCYCLINE | MELATONIN | METHAZOLAMIDE | HYDROXYCHLOROQUINE | ITTC | DMARDS | OBESE_HST | MORBIDOBESE_HST | PH_HST | AFIB_HST | COPD_HST | CHF_HST | DIAB_HST | CAD_HST | OSTEO_HST | HTN_HST | CANCER_HST | LUNG_CANCER_HST | OVARIAN_CANCER_HST | HEAD_NECK_CANCER_HST | BREAST_CANCER_HST | ASTHMA_HST | GERD_HST | FIBROMYALGIA_HST | DEPRESSION_HST | PSORIATIC_ARTHRITIS_HST | RHEUM_ARTHRITIS_HST | LUPUS_HST | VTVF_HST | STROKE_HST | VASCULARDISEASE_HST | LOWBACKPAIN_HST | DVT_HST | PE_HST | HYPOTHYROIDISM_HST | ADRENAL_INSUFFICIENCY_HST | INFERTILITY_HST | CKD_HST | ESRD_HST | OBS_SLEEPAPNEA_HST | CARDIAC_ARREST_HST | HEMO_STROKE_HST | MAJOR_BLEED_HST | MACULAR_DEGEN_HST | ANXIETY_HST | HYPERLIPIDEMIA_HST | HIV_HST | ALZHEIMER_HST | COLORECTAL_CANCER_HST | ENDOMETRIAL_CANCER_HST | GLAUCOMA_HST | HIP_PELVIC_FRACTURE_HST | BENIGN_PROSTATIC_HYPERPLASIA_HST | CIRRHOSIS_HST | CIRRHOSIS_HST_1 | CHOLESTEROL_CLOSEST | HDL_CLOSEST | LDL_CLOSEST | TRIG_CLOSEST | WBC_CLOSEST | HGB_CLOSEST | URIC_ACID_CLOSEST | HCO3_CLOSEST | SODIUM_CLOSEST | CREATININE_CLOSEST | EF_CLOSEST | FEV1_CLOSEST | EOS_CLOSEST | NEUTRO_CLOSEST | MONO_CLOSEST | BASOPHIL_CLOSEST | K_CLOSEST | EGFR_CLOSEST | TSH_CLOSEST | T4_CLOSEST | GLUCOSE_CLOSEST | HBA1C_CLOSEST | ESR_CLOSEST | VITAMIN_D_CLOSEST | MAGNESIUM_CLOSEST | FOLICAC_CLOSEST | VIT_B12_CLOSEST | BNP_CLOSEST | PLATELET_CLOSEST | PA_PRESSURE_CLOSEST | HEMATOCRIT_CLOSEST | ALBUMIN_CLOSEST | PREALBUMIN_CLOSEST | MR_CLOSEST | TR_CLOSEST | MEANPLATELETVOL_CLOSEST | MCH_CLOSEST | RDW_CLOSEST | MCV_CLOSEST | MCHC_CLOSEST | RBC_CLOSEST | LYMPHOCYTE_CLOSEST | CA125_CLOSEST | BILIRUBIN_CLOSEST | ALT_CLOSEST | AST_CLOSEST | CA_CLOSEST | PHOSPHORUS_CLOSEST | URINEPROTEIN_CLOSEST | TOTALPREVIOUSHOSPVISITS | TOTALPREVIOUSEDVISITS | TOTALPREVIOUSPCPVISITS | PREVIOUSSPECIALTYVISIT | PREVIOUSURGENTCAREVISIT | CAV_REC_SEX | CAV_REC_LANG | CAV_REC_AGE | CAV_REC_IPOP | CAV_REC_PRIORITY_CODE | CAV_REC_DISP_CODE | UREA_NITROGEN_MAX_1 | UREA_NITROGEN_MIN_1 | CALCIUM_MAX_1 | CALCIUM_MIN_1 | IRON_MAX_1 | IRON_MIN_1 | GLUCOSE_MAX_1 | GLUCOSE_MIN_1 | HGB_MAX_1 | HGB_MIN_1 | HEMATOCRIT_MAX_1 | HEMATOCRIT_MIN_1 | CHLORIDE_MAX_1 | CHLORIDE_MIN_1 | SODIUM_MAX_1 | SODIUM_MIN_1 | CREATININE_MAX_1 | CREATININE_MIN_1 | CARBON_DIOXIDE_MAX_1 | CARBON_DIOXIDE_MIN_1 | RBC_MAX_1 | RBC_MIN_1 | MCV_MAX_1 | MCV_MIN_1 | MCH_MAX_1 | MCH_MIN_1 | MCHC_MAX_1 | MCHC_MIN_1 | ANION_GAP_MAX_1 | ANION_GAP_MIN_1 | PLATELETS_MAX_1 | PLATELETS_MIN_1 | WBC_MAX_1 | WBC_MIN_1 | MEAN_PLATELET_VOLUME_MAX_1 | MEAN_PLATELET_VOLUME_MIN_1 | EGFR_MAX_1 | EGFR_MIN_1 | RDW_MAX_1 | RDW_MIN_1 | BASOPHILS_MAX_1 | BASOPHILS_MIN_1 | NEUTROPHILS_MAX_1 | NEUTROPHILS_MIN_1 | LYMPHOCYTES_MAX_1 | LYMPHOCYTES_MIN_1 | MONOCYTES_MAX_1 | MONOCYTES_MIN_1 | EOSINOPHILS_MAX_1 | EOSINOPHILS_MIN_1 | MAGNESIUM_MAX_1 | MAGNESIUM_MIN_1 | PHOSPHORUS_MAX_1 | PHOSPHORUS_MIN_1 | INR_MAX_1 | INR_MIN_1 | ALBUMIN_MAX_1 | ALBUMIN_MIN_1 | TOTAL_BILIRUBIN_MAX_1 | TOTAL_BILIRUBIN_MIN_1 | AST_MAX_1 | AST_MIN_1 | ALT_MAX_1 | ALT_MIN_1 | ALKALINE_PHOSPHATASE_MAX_1 | ALKALINE_PHOSPHATASE_MIN_1 | TOTAL_PROTEIN_MAX_1 | TOTAL_PROTEIN_MIN_1 | BUN_CREATININE_RATIO_MAX_1 | ACTIVATED_PTT_MAX_1 | BUN_CREATININE_RATIO_MIN_1 | ACTIVATED_PTT_MIN_1 | TROPONIN_I_MAX_1 | TROPONIN_I_MIN_1 | SPECIFIC_GRAVITY_URINE_MAX_1 | SPECIFIC_GRAVITY_URINE_MIN_1 | PROTEIN_URINE_MAX_1 | PROTEIN_URINE_MIN_1 | PH_URINE_MAX_1 | PH_URINE_MIN_1 | KETONES_URINE_MAX_1 | KETONES_URINE_MIN_1 | URINE_NITRITE_MAX_1 | URINE_NITRITE_MIN_1 | LEUKOCYTE_ESTERASE_MAX_1 | LEUKOCYTE_ESTERASE_MIN_1 | BLOOD_URINE_MAX_1 | BLOOD_URINE_MIN_1 | BILIRUBIN_URINE_MAX_1 | BILIRUBIN_URINE_MIN_1 | UROBILINOGEN_URINE_MAX_1 | UROBILINOGEN_URINE_MIN_1 | WHITE_BLOOD_CELLS_URINE_MAX_1 | WHITE_BLOOD_CELLS_URINE_MIN_1 | RED_BLOOD_CELLS_URINE_MAX_1 | RED_BLOOD_CELLS_URINE_MIN_1 | CALCULATED_OSMOLALITY_MAX_1 | CALCULATED_OSMOLALITY_MIN_1 | DIRECT_BILIRUBIN_MAX_1 | DIRECT_BILIRUBIN_MIN_1 | LACTATE_BLOOD_MAX_1 | LACTATE_BLOOD_MIN_1 | BACTERIA_MAX_1 | BACTERIA_MIN_1 | EPITHELIAL_CELLS_MAX_1 | EPITHELIAL_CELLS_MIN_1 | AG_RATIO_MAX_1 | AG_RATIO_MIN_1 | PCO2_ARTERIAL_MAX_1 | PCO2_ARTERIAL_MIN_1 | ADI_2015 | LOS | LOS_Binary | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2 | 16 | 2 | 2/19/2018 0:00 | 0 | 2/13/2018 20:04 | 2/19/2018 7:00 | 640 | 0 | 73.3 | 28.21 | 3056.0 | 102.0 | 70.0 | 83.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 169.0 | 28.0 | 101.0 | 201.0 | 4.7 | 13.9 | NaN | 23.0 | 137.0 | 1.22 | 76.0 | NaN | 1.5 | 47.0 | 15.6 | 0.6 | 4.2 | 58.0 | NaN | NaN | 91.0 | 5.6 | NaN | NaN | 1.6 | NaN | NaN | NaN | 145.0 | 40.0 | 41.4 | 3.2 | NaN | 2.0 | 2.0 | 7.6 | 30.9 | 16.7 | 91.9 | 33.7 | 4.51 | 35.3 | NaN | 0.6 | 13.0 | 26.0 | 9.0 | NaN | NaN | 1.0 | NaN | NaN | 3.0 | NaN | 1 | 13 | 72.0 | 3 | 3 | 10 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 68.493519 | 7.660417 | 1 |
| 1 | 28 | 16 | 2 | 2/22/2018 0:00 | 12 | 1/23/2018 9:27 | 2/22/2018 8:00 | 1314 | 1 | 26.1 | 25.61 | 2240.0 | 96.0 | 58.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 6.2 | 11.0 | NaN | NaN | NaN | NaN | NaN | NaN | 0.4 | 74.6 | 6.5 | 0.3 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 177.0 | NaN | 32.1 | NaN | NaN | NaN | NaN | 7.7 | 31.1 | 13.2 | 91.3 | 34.1 | 3.52 | 18.2 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 8.0 | NaN | 0 | 13 | 23.0 | 3 | 8 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 75.203533 | 2.575000 | 0 |
| 2 | 40 | 16 | 0 | 3/27/2018 0:00 | 16 | 3/6/2018 11:02 | 3/27/2018 7:15 | 1097 | 1 | 19.0 | 37.76 | 3520.0 | NaN | NaN | NaN | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 7.6 | 10.1 | NaN | 28.0 | 139.0 | 0.62 | NaN | NaN | 0.0 | 73.0 | 11.0 | 0.0 | 4.2 | 153.0 | NaN | NaN | 104.0 | NaN | NaN | NaN | 2.3 | NaN | NaN | NaN | 446.0 | NaN | 30.2 | 3.2 | NaN | NaN | NaN | 7.0 | 30.0 | 14.2 | 89.3 | 33.5 | 3.38 | 15.0 | NaN | 0.2 | 26.0 | 14.0 | 9.1 | 3.5 | NaN | 2.0 | NaN | NaN | 2.0 | NaN | 0 | 13 | 18.0 | 3 | 5 | 10 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 59.740571 | 3.552083 | 0 |
| 3 | 40 | 16 | 2 | 6/8/2017 0:00 | 16 | 6/6/2017 14:19 | 6/8/2017 13:00 | 980 | 0 | 74.1 | 29.53 | 3200.0 | NaN | NaN | NaN | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 11.8 | 8.7 | 4.1 | 17.0 | 119.0 | 1.56 | 60.0 | NaN | 5.0 | NaN | 13.0 | 0.0 | 5.2 | 43.0 | 0.426 | NaN | 139.0 | NaN | 11.0 | NaN | 2.6 | 24.8 | 1195.0 | 441.0 | 198.0 | 49.0 | 25.5 | 3.5 | 15.0 | 2.0 | 2.0 | 8.3 | 29.8 | 15.7 | 90.7 | 32.8 | 2.80 | 5.0 | NaN | 0.3 | 15.0 | 13.0 | 8.5 | 4.7 | NaN | 4.0 | NaN | NaN | 8.0 | NaN | 1 | 13 | 73.0 | 3 | 5 | 10 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 44.761703 | 5.778472 | 1 |
| 4 | 9 | 16 | 2 | 12/20/2017 0:00 | 3 | 12/7/2017 13:52 | 12/20/2017 10:00 | 1097 | 0 | 57.8 | 26.91 | 3398.4 | 120.0 | 60.0 | NaN | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 183.0 | 66.0 | 106.0 | 54.0 | 7.9 | 14.3 | NaN | 30.0 | 139.0 | 0.85 | NaN | NaN | 1.0 | 60.0 | 9.0 | 1.0 | 3.7 | 59.0 | NaN | NaN | 86.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 205.0 | NaN | 41.5 | 3.8 | 24.0 | NaN | NaN | 8.1 | 30.8 | 13.2 | 89.5 | 34.4 | 4.64 | 29.0 | NaN | 1.2 | 8.0 | 15.0 | 8.3 | NaN | NaN | NaN | NaN | 3.0 | 4.0 | NaN | 1 | 13 | 51.0 | 1 | 3 | 30 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 44.718861 | 1.626389 | 0 |
# Splitting the data into training and testing
from sklearn.model_selection import train_test_split
x_train, x_test, y_train, y_test = train_test_split(train_df.drop(columns = ['LOS', 'LOS_Binary', 'PROC_DATE', 'CREATE_DT_TM', 'SCHED_START_DT_TM']),
train_df['LOS_Binary'],
test_size=0.2,
random_state=1)
# Again, splitting into train and validation
x_train, x_val, y_train, y_val = train_test_split(x_train, y_train, test_size = 0.2, random_state = 1)
x_train_cat = x_train.copy()
x_train_cat[['SCHED_SURG_AREA', 'RACE', 'ETHNIC_GROUP', 'SCHED_HOSPITAL', 'SCHED_SURG_PROC_CD', 'FEMALE', 'PCPVISIT', 'METFORMIN_FLAG', 'OPIOIDS_FLAG', 'ALPHA_BLOCKERS', 'CENTRAL_ANTAGONISTS', 'RENIN', 'BETA_BLOCKERS', 'ACE_INHIB', 'ARB', 'ALDOSTERONE_BLOCKERS', 'VASODIALATORS', 'DIURETICS', 'CALCIUM_BLOCKERS', 'STATINS', 'INSULIN_MEDS', 'ASPIRIN', 'WARFARIN', 'DOACS', 'PRETERM_17P', 'MEDROL', 'PREDNISONE', 'INHALED_STEROID_WITH_LABA', 'INHALED_STEROID_WITHOUT_LABA', 'INHALED_STEROIDS', 'ASTHMA_BIOLOGICS', 'SHORT_ACTING_BRONCHO_DIALATORS', 'TNF_INHIBITORS', 'IMMUNOMODULATORS', 'AMINOSALICYLATES', 'CORTICOSTEROIDS', 'ARNI', 'ALLOPURINOL', 'SEIZURE', 'MUSCLERELAXANT', 'DIGOXIN', 'INOTROPES', 'ANTI_ARRHYTHMIC', 'ANTIPLATELET', 'SULFONYLUREA', 'GLP_1_AGONIST', 'THIAZOLIDINEDIONE', 'SGLT2_INHIBITOR', 'DPP4_INHIBITOR', 'ALPHA_GLUCOSIDASE_INHIBITOR', 'AMYLINOMIMETIC', 'RAPID_ACTING_INSULIN', 'SHORT_ACTING_INSULIN', 'INTERMEDIATE_ACTING_INSULIN', 'LONG_ACTING_INSULIN', 'MINOCYCLINE', 'DOXYCYCLINE', 'MELATONIN', 'METHAZOLAMIDE', 'HYDROXYCHLOROQUINE', 'ITTC', 'DMARDS', 'OBESE_HST', 'MORBIDOBESE_HST', 'PH_HST', 'AFIB_HST', 'COPD_HST', 'CHF_HST', 'DIAB_HST', 'CAD_HST', 'OSTEO_HST', 'HTN_HST', 'CANCER_HST', 'LUNG_CANCER_HST', 'OVARIAN_CANCER_HST', 'HEAD_NECK_CANCER_HST', 'BREAST_CANCER_HST', 'ASTHMA_HST', 'GERD_HST', 'FIBROMYALGIA_HST', 'DEPRESSION_HST', 'PSORIATIC_ARTHRITIS_HST', 'RHEUM_ARTHRITIS_HST', 'LUPUS_HST', 'VTVF_HST', 'STROKE_HST', 'VASCULARDISEASE_HST', 'LOWBACKPAIN_HST', 'DVT_HST', 'PE_HST', 'HYPOTHYROIDISM_HST', 'ADRENAL_INSUFFICIENCY_HST', 'INFERTILITY_HST', 'CKD_HST', 'ESRD_HST', 'OBS_SLEEPAPNEA_HST', 'CARDIAC_ARREST_HST', 'HEMO_STROKE_HST', 'MAJOR_BLEED_HST', 'MACULAR_DEGEN_HST', 'ANXIETY_HST', 'HYPERLIPIDEMIA_HST', 'HIV_HST', 'ALZHEIMER_HST', 'COLORECTAL_CANCER_HST', 'ENDOMETRIAL_CANCER_HST', 'GLAUCOMA_HST', 'HIP_PELVIC_FRACTURE_HST', 'BENIGN_PROSTATIC_HYPERPLASIA_HST', 'CIRRHOSIS_HST', 'CIRRHOSIS_HST_1', 'CAV_REC_SEX', 'CAV_REC_LANG', 'CAV_REC_IPOP', 'CAV_REC_PRIORITY_CODE', 'CAV_REC_DISP_CODE']] = x_train_cat[['SCHED_SURG_AREA', 'RACE', 'ETHNIC_GROUP', 'SCHED_HOSPITAL', 'SCHED_SURG_PROC_CD', 'FEMALE', 'PCPVISIT', 'METFORMIN_FLAG', 'OPIOIDS_FLAG', 'ALPHA_BLOCKERS', 'CENTRAL_ANTAGONISTS', 'RENIN', 'BETA_BLOCKERS', 'ACE_INHIB', 'ARB', 'ALDOSTERONE_BLOCKERS', 'VASODIALATORS', 'DIURETICS', 'CALCIUM_BLOCKERS', 'STATINS', 'INSULIN_MEDS', 'ASPIRIN', 'WARFARIN', 'DOACS', 'PRETERM_17P', 'MEDROL', 'PREDNISONE', 'INHALED_STEROID_WITH_LABA', 'INHALED_STEROID_WITHOUT_LABA', 'INHALED_STEROIDS', 'ASTHMA_BIOLOGICS', 'SHORT_ACTING_BRONCHO_DIALATORS', 'TNF_INHIBITORS', 'IMMUNOMODULATORS', 'AMINOSALICYLATES', 'CORTICOSTEROIDS', 'ARNI', 'ALLOPURINOL', 'SEIZURE', 'MUSCLERELAXANT', 'DIGOXIN', 'INOTROPES', 'ANTI_ARRHYTHMIC', 'ANTIPLATELET', 'SULFONYLUREA', 'GLP_1_AGONIST', 'THIAZOLIDINEDIONE', 'SGLT2_INHIBITOR', 'DPP4_INHIBITOR', 'ALPHA_GLUCOSIDASE_INHIBITOR', 'AMYLINOMIMETIC', 'RAPID_ACTING_INSULIN', 'SHORT_ACTING_INSULIN', 'INTERMEDIATE_ACTING_INSULIN', 'LONG_ACTING_INSULIN', 'MINOCYCLINE', 'DOXYCYCLINE', 'MELATONIN', 'METHAZOLAMIDE', 'HYDROXYCHLOROQUINE', 'ITTC', 'DMARDS', 'OBESE_HST', 'MORBIDOBESE_HST', 'PH_HST', 'AFIB_HST', 'COPD_HST', 'CHF_HST', 'DIAB_HST', 'CAD_HST', 'OSTEO_HST', 'HTN_HST', 'CANCER_HST', 'LUNG_CANCER_HST', 'OVARIAN_CANCER_HST', 'HEAD_NECK_CANCER_HST', 'BREAST_CANCER_HST', 'ASTHMA_HST', 'GERD_HST', 'FIBROMYALGIA_HST', 'DEPRESSION_HST', 'PSORIATIC_ARTHRITIS_HST', 'RHEUM_ARTHRITIS_HST', 'LUPUS_HST', 'VTVF_HST', 'STROKE_HST', 'VASCULARDISEASE_HST', 'LOWBACKPAIN_HST', 'DVT_HST', 'PE_HST', 'HYPOTHYROIDISM_HST', 'ADRENAL_INSUFFICIENCY_HST', 'INFERTILITY_HST', 'CKD_HST', 'ESRD_HST', 'OBS_SLEEPAPNEA_HST', 'CARDIAC_ARREST_HST', 'HEMO_STROKE_HST', 'MAJOR_BLEED_HST', 'MACULAR_DEGEN_HST', 'ANXIETY_HST', 'HYPERLIPIDEMIA_HST', 'HIV_HST', 'ALZHEIMER_HST', 'COLORECTAL_CANCER_HST', 'ENDOMETRIAL_CANCER_HST', 'GLAUCOMA_HST', 'HIP_PELVIC_FRACTURE_HST', 'BENIGN_PROSTATIC_HYPERPLASIA_HST', 'CIRRHOSIS_HST', 'CIRRHOSIS_HST_1', 'CAV_REC_SEX', 'CAV_REC_LANG', 'CAV_REC_IPOP', 'CAV_REC_PRIORITY_CODE', 'CAV_REC_DISP_CODE']].astype(str)
x_val_cat = x_val.copy()
x_val_cat[['SCHED_SURG_AREA', 'RACE', 'ETHNIC_GROUP', 'SCHED_HOSPITAL', 'SCHED_SURG_PROC_CD', 'FEMALE', 'PCPVISIT', 'METFORMIN_FLAG', 'OPIOIDS_FLAG', 'ALPHA_BLOCKERS', 'CENTRAL_ANTAGONISTS', 'RENIN', 'BETA_BLOCKERS', 'ACE_INHIB', 'ARB', 'ALDOSTERONE_BLOCKERS', 'VASODIALATORS', 'DIURETICS', 'CALCIUM_BLOCKERS', 'STATINS', 'INSULIN_MEDS', 'ASPIRIN', 'WARFARIN', 'DOACS', 'PRETERM_17P', 'MEDROL', 'PREDNISONE', 'INHALED_STEROID_WITH_LABA', 'INHALED_STEROID_WITHOUT_LABA', 'INHALED_STEROIDS', 'ASTHMA_BIOLOGICS', 'SHORT_ACTING_BRONCHO_DIALATORS', 'TNF_INHIBITORS', 'IMMUNOMODULATORS', 'AMINOSALICYLATES', 'CORTICOSTEROIDS', 'ARNI', 'ALLOPURINOL', 'SEIZURE', 'MUSCLERELAXANT', 'DIGOXIN', 'INOTROPES', 'ANTI_ARRHYTHMIC', 'ANTIPLATELET', 'SULFONYLUREA', 'GLP_1_AGONIST', 'THIAZOLIDINEDIONE', 'SGLT2_INHIBITOR', 'DPP4_INHIBITOR', 'ALPHA_GLUCOSIDASE_INHIBITOR', 'AMYLINOMIMETIC', 'RAPID_ACTING_INSULIN', 'SHORT_ACTING_INSULIN', 'INTERMEDIATE_ACTING_INSULIN', 'LONG_ACTING_INSULIN', 'MINOCYCLINE', 'DOXYCYCLINE', 'MELATONIN', 'METHAZOLAMIDE', 'HYDROXYCHLOROQUINE', 'ITTC', 'DMARDS', 'OBESE_HST', 'MORBIDOBESE_HST', 'PH_HST', 'AFIB_HST', 'COPD_HST', 'CHF_HST', 'DIAB_HST', 'CAD_HST', 'OSTEO_HST', 'HTN_HST', 'CANCER_HST', 'LUNG_CANCER_HST', 'OVARIAN_CANCER_HST', 'HEAD_NECK_CANCER_HST', 'BREAST_CANCER_HST', 'ASTHMA_HST', 'GERD_HST', 'FIBROMYALGIA_HST', 'DEPRESSION_HST', 'PSORIATIC_ARTHRITIS_HST', 'RHEUM_ARTHRITIS_HST', 'LUPUS_HST', 'VTVF_HST', 'STROKE_HST', 'VASCULARDISEASE_HST', 'LOWBACKPAIN_HST', 'DVT_HST', 'PE_HST', 'HYPOTHYROIDISM_HST', 'ADRENAL_INSUFFICIENCY_HST', 'INFERTILITY_HST', 'CKD_HST', 'ESRD_HST', 'OBS_SLEEPAPNEA_HST', 'CARDIAC_ARREST_HST', 'HEMO_STROKE_HST', 'MAJOR_BLEED_HST', 'MACULAR_DEGEN_HST', 'ANXIETY_HST', 'HYPERLIPIDEMIA_HST', 'HIV_HST', 'ALZHEIMER_HST', 'COLORECTAL_CANCER_HST', 'ENDOMETRIAL_CANCER_HST', 'GLAUCOMA_HST', 'HIP_PELVIC_FRACTURE_HST', 'BENIGN_PROSTATIC_HYPERPLASIA_HST', 'CIRRHOSIS_HST', 'CIRRHOSIS_HST_1', 'CAV_REC_SEX', 'CAV_REC_LANG', 'CAV_REC_IPOP', 'CAV_REC_PRIORITY_CODE', 'CAV_REC_DISP_CODE']] = x_val_cat[['SCHED_SURG_AREA', 'RACE', 'ETHNIC_GROUP', 'SCHED_HOSPITAL', 'SCHED_SURG_PROC_CD', 'FEMALE', 'PCPVISIT', 'METFORMIN_FLAG', 'OPIOIDS_FLAG', 'ALPHA_BLOCKERS', 'CENTRAL_ANTAGONISTS', 'RENIN', 'BETA_BLOCKERS', 'ACE_INHIB', 'ARB', 'ALDOSTERONE_BLOCKERS', 'VASODIALATORS', 'DIURETICS', 'CALCIUM_BLOCKERS', 'STATINS', 'INSULIN_MEDS', 'ASPIRIN', 'WARFARIN', 'DOACS', 'PRETERM_17P', 'MEDROL', 'PREDNISONE', 'INHALED_STEROID_WITH_LABA', 'INHALED_STEROID_WITHOUT_LABA', 'INHALED_STEROIDS', 'ASTHMA_BIOLOGICS', 'SHORT_ACTING_BRONCHO_DIALATORS', 'TNF_INHIBITORS', 'IMMUNOMODULATORS', 'AMINOSALICYLATES', 'CORTICOSTEROIDS', 'ARNI', 'ALLOPURINOL', 'SEIZURE', 'MUSCLERELAXANT', 'DIGOXIN', 'INOTROPES', 'ANTI_ARRHYTHMIC', 'ANTIPLATELET', 'SULFONYLUREA', 'GLP_1_AGONIST', 'THIAZOLIDINEDIONE', 'SGLT2_INHIBITOR', 'DPP4_INHIBITOR', 'ALPHA_GLUCOSIDASE_INHIBITOR', 'AMYLINOMIMETIC', 'RAPID_ACTING_INSULIN', 'SHORT_ACTING_INSULIN', 'INTERMEDIATE_ACTING_INSULIN', 'LONG_ACTING_INSULIN', 'MINOCYCLINE', 'DOXYCYCLINE', 'MELATONIN', 'METHAZOLAMIDE', 'HYDROXYCHLOROQUINE', 'ITTC', 'DMARDS', 'OBESE_HST', 'MORBIDOBESE_HST', 'PH_HST', 'AFIB_HST', 'COPD_HST', 'CHF_HST', 'DIAB_HST', 'CAD_HST', 'OSTEO_HST', 'HTN_HST', 'CANCER_HST', 'LUNG_CANCER_HST', 'OVARIAN_CANCER_HST', 'HEAD_NECK_CANCER_HST', 'BREAST_CANCER_HST', 'ASTHMA_HST', 'GERD_HST', 'FIBROMYALGIA_HST', 'DEPRESSION_HST', 'PSORIATIC_ARTHRITIS_HST', 'RHEUM_ARTHRITIS_HST', 'LUPUS_HST', 'VTVF_HST', 'STROKE_HST', 'VASCULARDISEASE_HST', 'LOWBACKPAIN_HST', 'DVT_HST', 'PE_HST', 'HYPOTHYROIDISM_HST', 'ADRENAL_INSUFFICIENCY_HST', 'INFERTILITY_HST', 'CKD_HST', 'ESRD_HST', 'OBS_SLEEPAPNEA_HST', 'CARDIAC_ARREST_HST', 'HEMO_STROKE_HST', 'MAJOR_BLEED_HST', 'MACULAR_DEGEN_HST', 'ANXIETY_HST', 'HYPERLIPIDEMIA_HST', 'HIV_HST', 'ALZHEIMER_HST', 'COLORECTAL_CANCER_HST', 'ENDOMETRIAL_CANCER_HST', 'GLAUCOMA_HST', 'HIP_PELVIC_FRACTURE_HST', 'BENIGN_PROSTATIC_HYPERPLASIA_HST', 'CIRRHOSIS_HST', 'CIRRHOSIS_HST_1', 'CAV_REC_SEX', 'CAV_REC_LANG', 'CAV_REC_IPOP', 'CAV_REC_PRIORITY_CODE', 'CAV_REC_DISP_CODE']].astype(str)
x_test_cat = x_test.copy()
x_test_cat[['SCHED_SURG_AREA', 'RACE', 'ETHNIC_GROUP', 'SCHED_HOSPITAL', 'SCHED_SURG_PROC_CD', 'FEMALE', 'PCPVISIT', 'METFORMIN_FLAG', 'OPIOIDS_FLAG', 'ALPHA_BLOCKERS', 'CENTRAL_ANTAGONISTS', 'RENIN', 'BETA_BLOCKERS', 'ACE_INHIB', 'ARB', 'ALDOSTERONE_BLOCKERS', 'VASODIALATORS', 'DIURETICS', 'CALCIUM_BLOCKERS', 'STATINS', 'INSULIN_MEDS', 'ASPIRIN', 'WARFARIN', 'DOACS', 'PRETERM_17P', 'MEDROL', 'PREDNISONE', 'INHALED_STEROID_WITH_LABA', 'INHALED_STEROID_WITHOUT_LABA', 'INHALED_STEROIDS', 'ASTHMA_BIOLOGICS', 'SHORT_ACTING_BRONCHO_DIALATORS', 'TNF_INHIBITORS', 'IMMUNOMODULATORS', 'AMINOSALICYLATES', 'CORTICOSTEROIDS', 'ARNI', 'ALLOPURINOL', 'SEIZURE', 'MUSCLERELAXANT', 'DIGOXIN', 'INOTROPES', 'ANTI_ARRHYTHMIC', 'ANTIPLATELET', 'SULFONYLUREA', 'GLP_1_AGONIST', 'THIAZOLIDINEDIONE', 'SGLT2_INHIBITOR', 'DPP4_INHIBITOR', 'ALPHA_GLUCOSIDASE_INHIBITOR', 'AMYLINOMIMETIC', 'RAPID_ACTING_INSULIN', 'SHORT_ACTING_INSULIN', 'INTERMEDIATE_ACTING_INSULIN', 'LONG_ACTING_INSULIN', 'MINOCYCLINE', 'DOXYCYCLINE', 'MELATONIN', 'METHAZOLAMIDE', 'HYDROXYCHLOROQUINE', 'ITTC', 'DMARDS', 'OBESE_HST', 'MORBIDOBESE_HST', 'PH_HST', 'AFIB_HST', 'COPD_HST', 'CHF_HST', 'DIAB_HST', 'CAD_HST', 'OSTEO_HST', 'HTN_HST', 'CANCER_HST', 'LUNG_CANCER_HST', 'OVARIAN_CANCER_HST', 'HEAD_NECK_CANCER_HST', 'BREAST_CANCER_HST', 'ASTHMA_HST', 'GERD_HST', 'FIBROMYALGIA_HST', 'DEPRESSION_HST', 'PSORIATIC_ARTHRITIS_HST', 'RHEUM_ARTHRITIS_HST', 'LUPUS_HST', 'VTVF_HST', 'STROKE_HST', 'VASCULARDISEASE_HST', 'LOWBACKPAIN_HST', 'DVT_HST', 'PE_HST', 'HYPOTHYROIDISM_HST', 'ADRENAL_INSUFFICIENCY_HST', 'INFERTILITY_HST', 'CKD_HST', 'ESRD_HST', 'OBS_SLEEPAPNEA_HST', 'CARDIAC_ARREST_HST', 'HEMO_STROKE_HST', 'MAJOR_BLEED_HST', 'MACULAR_DEGEN_HST', 'ANXIETY_HST', 'HYPERLIPIDEMIA_HST', 'HIV_HST', 'ALZHEIMER_HST', 'COLORECTAL_CANCER_HST', 'ENDOMETRIAL_CANCER_HST', 'GLAUCOMA_HST', 'HIP_PELVIC_FRACTURE_HST', 'BENIGN_PROSTATIC_HYPERPLASIA_HST', 'CIRRHOSIS_HST', 'CIRRHOSIS_HST_1', 'CAV_REC_SEX', 'CAV_REC_LANG', 'CAV_REC_IPOP', 'CAV_REC_PRIORITY_CODE', 'CAV_REC_DISP_CODE']] = x_test_cat[['SCHED_SURG_AREA', 'RACE', 'ETHNIC_GROUP', 'SCHED_HOSPITAL', 'SCHED_SURG_PROC_CD', 'FEMALE', 'PCPVISIT', 'METFORMIN_FLAG', 'OPIOIDS_FLAG', 'ALPHA_BLOCKERS', 'CENTRAL_ANTAGONISTS', 'RENIN', 'BETA_BLOCKERS', 'ACE_INHIB', 'ARB', 'ALDOSTERONE_BLOCKERS', 'VASODIALATORS', 'DIURETICS', 'CALCIUM_BLOCKERS', 'STATINS', 'INSULIN_MEDS', 'ASPIRIN', 'WARFARIN', 'DOACS', 'PRETERM_17P', 'MEDROL', 'PREDNISONE', 'INHALED_STEROID_WITH_LABA', 'INHALED_STEROID_WITHOUT_LABA', 'INHALED_STEROIDS', 'ASTHMA_BIOLOGICS', 'SHORT_ACTING_BRONCHO_DIALATORS', 'TNF_INHIBITORS', 'IMMUNOMODULATORS', 'AMINOSALICYLATES', 'CORTICOSTEROIDS', 'ARNI', 'ALLOPURINOL', 'SEIZURE', 'MUSCLERELAXANT', 'DIGOXIN', 'INOTROPES', 'ANTI_ARRHYTHMIC', 'ANTIPLATELET', 'SULFONYLUREA', 'GLP_1_AGONIST', 'THIAZOLIDINEDIONE', 'SGLT2_INHIBITOR', 'DPP4_INHIBITOR', 'ALPHA_GLUCOSIDASE_INHIBITOR', 'AMYLINOMIMETIC', 'RAPID_ACTING_INSULIN', 'SHORT_ACTING_INSULIN', 'INTERMEDIATE_ACTING_INSULIN', 'LONG_ACTING_INSULIN', 'MINOCYCLINE', 'DOXYCYCLINE', 'MELATONIN', 'METHAZOLAMIDE', 'HYDROXYCHLOROQUINE', 'ITTC', 'DMARDS', 'OBESE_HST', 'MORBIDOBESE_HST', 'PH_HST', 'AFIB_HST', 'COPD_HST', 'CHF_HST', 'DIAB_HST', 'CAD_HST', 'OSTEO_HST', 'HTN_HST', 'CANCER_HST', 'LUNG_CANCER_HST', 'OVARIAN_CANCER_HST', 'HEAD_NECK_CANCER_HST', 'BREAST_CANCER_HST', 'ASTHMA_HST', 'GERD_HST', 'FIBROMYALGIA_HST', 'DEPRESSION_HST', 'PSORIATIC_ARTHRITIS_HST', 'RHEUM_ARTHRITIS_HST', 'LUPUS_HST', 'VTVF_HST', 'STROKE_HST', 'VASCULARDISEASE_HST', 'LOWBACKPAIN_HST', 'DVT_HST', 'PE_HST', 'HYPOTHYROIDISM_HST', 'ADRENAL_INSUFFICIENCY_HST', 'INFERTILITY_HST', 'CKD_HST', 'ESRD_HST', 'OBS_SLEEPAPNEA_HST', 'CARDIAC_ARREST_HST', 'HEMO_STROKE_HST', 'MAJOR_BLEED_HST', 'MACULAR_DEGEN_HST', 'ANXIETY_HST', 'HYPERLIPIDEMIA_HST', 'HIV_HST', 'ALZHEIMER_HST', 'COLORECTAL_CANCER_HST', 'ENDOMETRIAL_CANCER_HST', 'GLAUCOMA_HST', 'HIP_PELVIC_FRACTURE_HST', 'BENIGN_PROSTATIC_HYPERPLASIA_HST', 'CIRRHOSIS_HST', 'CIRRHOSIS_HST_1', 'CAV_REC_SEX', 'CAV_REC_LANG', 'CAV_REC_IPOP', 'CAV_REC_PRIORITY_CODE', 'CAV_REC_DISP_CODE']].astype(str)
# Checking sample data
x_train.head(20)
| SCHED_SURG_AREA | RACE | ETHNIC_GROUP | SCHED_HOSPITAL | SCHED_SURG_PROC_CD | FEMALE | AGE_ON_CONTACT_DATE | BMI | WEIGHT | BP_SYSTOLIC | BP_DIASTOLIC | PULSE | PCPVISIT | METFORMIN_FLAG | OPIOIDS_FLAG | ALPHA_BLOCKERS | CENTRAL_ANTAGONISTS | RENIN | BETA_BLOCKERS | ACE_INHIB | ARB | ALDOSTERONE_BLOCKERS | VASODIALATORS | DIURETICS | CALCIUM_BLOCKERS | STATINS | INSULIN_MEDS | ASPIRIN | WARFARIN | DOACS | PRETERM_17P | MEDROL | PREDNISONE | INHALED_STEROID_WITH_LABA | INHALED_STEROID_WITHOUT_LABA | INHALED_STEROIDS | ASTHMA_BIOLOGICS | SHORT_ACTING_BRONCHO_DIALATORS | TNF_INHIBITORS | IMMUNOMODULATORS | AMINOSALICYLATES | CORTICOSTEROIDS | ARNI | ALLOPURINOL | SEIZURE | MUSCLERELAXANT | DIGOXIN | INOTROPES | ANTI_ARRHYTHMIC | ANTIPLATELET | SULFONYLUREA | GLP_1_AGONIST | THIAZOLIDINEDIONE | SGLT2_INHIBITOR | DPP4_INHIBITOR | ALPHA_GLUCOSIDASE_INHIBITOR | AMYLINOMIMETIC | RAPID_ACTING_INSULIN | SHORT_ACTING_INSULIN | INTERMEDIATE_ACTING_INSULIN | LONG_ACTING_INSULIN | MINOCYCLINE | DOXYCYCLINE | MELATONIN | METHAZOLAMIDE | HYDROXYCHLOROQUINE | ITTC | DMARDS | OBESE_HST | MORBIDOBESE_HST | PH_HST | AFIB_HST | COPD_HST | CHF_HST | DIAB_HST | CAD_HST | OSTEO_HST | HTN_HST | CANCER_HST | LUNG_CANCER_HST | OVARIAN_CANCER_HST | HEAD_NECK_CANCER_HST | BREAST_CANCER_HST | ASTHMA_HST | GERD_HST | FIBROMYALGIA_HST | DEPRESSION_HST | PSORIATIC_ARTHRITIS_HST | RHEUM_ARTHRITIS_HST | LUPUS_HST | VTVF_HST | STROKE_HST | VASCULARDISEASE_HST | LOWBACKPAIN_HST | DVT_HST | PE_HST | HYPOTHYROIDISM_HST | ADRENAL_INSUFFICIENCY_HST | INFERTILITY_HST | CKD_HST | ESRD_HST | OBS_SLEEPAPNEA_HST | CARDIAC_ARREST_HST | HEMO_STROKE_HST | MAJOR_BLEED_HST | MACULAR_DEGEN_HST | ANXIETY_HST | HYPERLIPIDEMIA_HST | HIV_HST | ALZHEIMER_HST | COLORECTAL_CANCER_HST | ENDOMETRIAL_CANCER_HST | GLAUCOMA_HST | HIP_PELVIC_FRACTURE_HST | BENIGN_PROSTATIC_HYPERPLASIA_HST | CIRRHOSIS_HST | CIRRHOSIS_HST_1 | CHOLESTEROL_CLOSEST | HDL_CLOSEST | LDL_CLOSEST | TRIG_CLOSEST | WBC_CLOSEST | HGB_CLOSEST | URIC_ACID_CLOSEST | HCO3_CLOSEST | SODIUM_CLOSEST | CREATININE_CLOSEST | EF_CLOSEST | FEV1_CLOSEST | EOS_CLOSEST | NEUTRO_CLOSEST | MONO_CLOSEST | BASOPHIL_CLOSEST | K_CLOSEST | EGFR_CLOSEST | TSH_CLOSEST | T4_CLOSEST | GLUCOSE_CLOSEST | HBA1C_CLOSEST | ESR_CLOSEST | VITAMIN_D_CLOSEST | MAGNESIUM_CLOSEST | FOLICAC_CLOSEST | VIT_B12_CLOSEST | BNP_CLOSEST | PLATELET_CLOSEST | PA_PRESSURE_CLOSEST | HEMATOCRIT_CLOSEST | ALBUMIN_CLOSEST | PREALBUMIN_CLOSEST | MR_CLOSEST | TR_CLOSEST | MEANPLATELETVOL_CLOSEST | MCH_CLOSEST | RDW_CLOSEST | MCV_CLOSEST | MCHC_CLOSEST | RBC_CLOSEST | LYMPHOCYTE_CLOSEST | CA125_CLOSEST | BILIRUBIN_CLOSEST | ALT_CLOSEST | AST_CLOSEST | CA_CLOSEST | PHOSPHORUS_CLOSEST | URINEPROTEIN_CLOSEST | TOTALPREVIOUSHOSPVISITS | TOTALPREVIOUSEDVISITS | TOTALPREVIOUSPCPVISITS | PREVIOUSSPECIALTYVISIT | PREVIOUSURGENTCAREVISIT | CAV_REC_SEX | CAV_REC_LANG | CAV_REC_AGE | CAV_REC_IPOP | CAV_REC_PRIORITY_CODE | CAV_REC_DISP_CODE | UREA_NITROGEN_MAX_1 | UREA_NITROGEN_MIN_1 | CALCIUM_MAX_1 | CALCIUM_MIN_1 | IRON_MAX_1 | IRON_MIN_1 | GLUCOSE_MAX_1 | GLUCOSE_MIN_1 | HGB_MAX_1 | HGB_MIN_1 | HEMATOCRIT_MAX_1 | HEMATOCRIT_MIN_1 | CHLORIDE_MAX_1 | CHLORIDE_MIN_1 | SODIUM_MAX_1 | SODIUM_MIN_1 | CREATININE_MAX_1 | CREATININE_MIN_1 | CARBON_DIOXIDE_MAX_1 | CARBON_DIOXIDE_MIN_1 | RBC_MAX_1 | RBC_MIN_1 | MCV_MAX_1 | MCV_MIN_1 | MCH_MAX_1 | MCH_MIN_1 | MCHC_MAX_1 | MCHC_MIN_1 | ANION_GAP_MAX_1 | ANION_GAP_MIN_1 | PLATELETS_MAX_1 | PLATELETS_MIN_1 | WBC_MAX_1 | WBC_MIN_1 | MEAN_PLATELET_VOLUME_MAX_1 | MEAN_PLATELET_VOLUME_MIN_1 | EGFR_MAX_1 | EGFR_MIN_1 | RDW_MAX_1 | RDW_MIN_1 | BASOPHILS_MAX_1 | BASOPHILS_MIN_1 | NEUTROPHILS_MAX_1 | NEUTROPHILS_MIN_1 | LYMPHOCYTES_MAX_1 | LYMPHOCYTES_MIN_1 | MONOCYTES_MAX_1 | MONOCYTES_MIN_1 | EOSINOPHILS_MAX_1 | EOSINOPHILS_MIN_1 | MAGNESIUM_MAX_1 | MAGNESIUM_MIN_1 | PHOSPHORUS_MAX_1 | PHOSPHORUS_MIN_1 | INR_MAX_1 | INR_MIN_1 | ALBUMIN_MAX_1 | ALBUMIN_MIN_1 | TOTAL_BILIRUBIN_MAX_1 | TOTAL_BILIRUBIN_MIN_1 | AST_MAX_1 | AST_MIN_1 | ALT_MAX_1 | ALT_MIN_1 | ALKALINE_PHOSPHATASE_MAX_1 | ALKALINE_PHOSPHATASE_MIN_1 | TOTAL_PROTEIN_MAX_1 | TOTAL_PROTEIN_MIN_1 | BUN_CREATININE_RATIO_MAX_1 | ACTIVATED_PTT_MAX_1 | BUN_CREATININE_RATIO_MIN_1 | ACTIVATED_PTT_MIN_1 | TROPONIN_I_MAX_1 | TROPONIN_I_MIN_1 | SPECIFIC_GRAVITY_URINE_MAX_1 | SPECIFIC_GRAVITY_URINE_MIN_1 | PROTEIN_URINE_MAX_1 | PROTEIN_URINE_MIN_1 | PH_URINE_MAX_1 | PH_URINE_MIN_1 | KETONES_URINE_MAX_1 | KETONES_URINE_MIN_1 | URINE_NITRITE_MAX_1 | URINE_NITRITE_MIN_1 | LEUKOCYTE_ESTERASE_MAX_1 | LEUKOCYTE_ESTERASE_MIN_1 | BLOOD_URINE_MAX_1 | BLOOD_URINE_MIN_1 | BILIRUBIN_URINE_MAX_1 | BILIRUBIN_URINE_MIN_1 | UROBILINOGEN_URINE_MAX_1 | UROBILINOGEN_URINE_MIN_1 | WHITE_BLOOD_CELLS_URINE_MAX_1 | WHITE_BLOOD_CELLS_URINE_MIN_1 | RED_BLOOD_CELLS_URINE_MAX_1 | RED_BLOOD_CELLS_URINE_MIN_1 | CALCULATED_OSMOLALITY_MAX_1 | CALCULATED_OSMOLALITY_MIN_1 | DIRECT_BILIRUBIN_MAX_1 | DIRECT_BILIRUBIN_MIN_1 | LACTATE_BLOOD_MAX_1 | LACTATE_BLOOD_MIN_1 | BACTERIA_MAX_1 | BACTERIA_MIN_1 | EPITHELIAL_CELLS_MAX_1 | EPITHELIAL_CELLS_MIN_1 | AG_RATIO_MAX_1 | AG_RATIO_MIN_1 | PCO2_ARTERIAL_MAX_1 | PCO2_ARTERIAL_MIN_1 | ADI_2015 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 36116 | 19 | 2 | 2 | 8 | 1404 | 1 | 63.1 | 16.47 | 1488.0 | 158.0 | 90.0 | 115.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 2.7 | 9.4 | NaN | 26.1 | 137.0 | 0.70 | NaN | NaN | NaN | NaN | NaN | NaN | 4.3 | 60.0 | NaN | NaN | 109.0 | NaN | NaN | NaN | 2.0 | NaN | NaN | NaN | 289.0 | NaN | 30.9 | 4.0 | NaN | NaN | NaN | 8.7 | 20.4 | 25.5 | 67.0 | 30.4 | 4.61 | NaN | NaN | 0.4 | 32.0 | 56.0 | 10.9 | 3.7 | 1.0 | 1.0 | NaN | NaN | 2.0 | NaN | 0 | 13 | 63.0 | 3 | 3 | 14 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 79.080879 |
| 13231 | 29 | 17 | 4 | 12 | 1015 | 2 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | NaN | NaN | NaN | 1 | 13 | 75.0 | 1 | 3 | 30 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 80.571579 |
| 56836 | 29 | 16 | 2 | 12 | 825 | 1 | 74.7 | 31.01 | 3360.0 | 110.0 | 54.0 | 99.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 110.0 | 24.0 | 45.0 | 203.0 | 4.6 | 10.0 | NaN | 25.0 | 138.0 | 2.01 | 60.0 | NaN | 2.5 | 65.1 | 8.2 | 0.4 | 4.7 | 24.0 | 2.080 | NaN | 177.0 | 8.2 | NaN | 18.00 | 2.0 | 20.0 | 1710.0 | NaN | 84.0 | 37.0 | 30.1 | 3.4 | 5.96 | 2.0 | 1.0 | 9.1 | 30.2 | 15.8 | 90.9 | 33.3 | 3.31 | 23.8 | NaN | 0.4 | 21.0 | 37.0 | 9.1 | 2.7 | 3.0 | 4.0 | 5.0 | 19.0 | 23.0 | NaN | 0 | 13 | 74.0 | 1 | 3 | 30 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 80.571579 |
| 61971 | 35 | 17 | 4 | 14 | 673 | 2 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1 | 13 | 43.0 | 2 | 15 | 15 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 50.716464 |
| 1532 | 19 | 2 | 2 | 8 | 1336 | 0 | 75.3 | 37.84 | 4160.0 | 135.0 | 90.0 | 86.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 6.2 | 11.9 | NaN | 29.0 | 145.0 | 1.21 | NaN | NaN | 3.9 | 66.4 | 10.4 | 0.2 | 3.9 | 58.0 | NaN | NaN | 92.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 146.0 | NaN | 36.9 | 3.1 | NaN | NaN | NaN | 8.5 | 28.0 | 13.4 | 84.5 | 33.1 | 4.37 | 19.1 | NaN | 0.7 | 20.0 | 18.0 | 8.6 | NaN | NaN | NaN | NaN | NaN | 6.0 | NaN | 1 | 13 | 74.0 | 4 | 3 | 30 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 62.224959 |
| 25029 | 10 | 16 | 2 | 3 | 1404 | 1 | 82.2 | NaN | NaN | NaN | NaN | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 188.0 | 71.0 | 102.0 | 65.0 | 3.1 | 14.1 | NaN | 26.0 | 128.0 | 0.95 | NaN | NaN | 2.0 | 58.0 | 11.0 | 1.0 | 4.3 | 59.0 | 3.410 | NaN | 100.0 | 5.3 | NaN | NaN | NaN | 24.0 | 811.0 | NaN | 133.0 | NaN | 40.5 | 3.8 | NaN | NaN | NaN | 8.4 | 31.8 | 13.4 | 91.5 | 34.8 | 4.43 | 28.0 | NaN | 0.6 | 21.0 | 15.0 | 8.8 | NaN | 0.0 | NaN | 7.0 | 4.0 | 2.0 | NaN | 0 | 13 | 82.0 | 1 | 3 | 30 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 95.235095 |
| 1059 | 37 | 16 | 2 | 15 | 1095 | 0 | 37.2 | 30.94 | 3856.0 | 122.0 | 89.0 | 84.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 8.8 | 14.8 | NaN | 25.0 | 138.0 | 0.87 | NaN | NaN | 5.5 | 51.0 | 9.7 | 0.7 | 3.8 | 128.0 | NaN | NaN | 83.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 271.0 | NaN | 42.8 | 3.9 | NaN | NaN | NaN | 8.6 | 30.0 | 13.1 | 87.0 | 34.5 | 4.92 | 33.1 | NaN | 0.3 | 32.0 | 20.0 | 9.1 | NaN | NaN | NaN | 1.0 | 7.0 | 8.0 | NaN | 1 | 13 | 36.0 | 1 | 3 | 30 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 60.770270 |
| 68346 | 35 | 16 | 2 | 14 | 1307 | 1 | 31.0 | 39.16 | 4000.0 | NaN | NaN | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 8.2 | 15.0 | NaN | 26.0 | 139.0 | 0.80 | 60.0 | NaN | 2.0 | 68.0 | 4.0 | 1.0 | 4.3 | 60.0 | NaN | NaN | 90.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 260.0 | 16.0 | 43.8 | 4.5 | 21.00 | 2.5 | 1.0 | 8.2 | 30.5 | 13.6 | 88.9 | 34.3 | 4.92 | 25.0 | NaN | 0.7 | 42.0 | 27.0 | 10.1 | NaN | NaN | NaN | 2.0 | NaN | 7.0 | NaN | 0 | 13 | 31.0 | 1 | 3 | 30 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 69.477321 |
| 23598 | 31 | 16 | 2 | 13 | 465 | 1 | 46.3 | 29.63 | 2592.0 | 127.0 | 87.0 | 111.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 247.0 | 36.0 | 157.0 | 270.0 | 14.5 | 15.0 | NaN | 21.0 | 134.0 | 0.70 | NaN | NaN | 2.0 | 76.0 | 6.0 | 0.0 | 5.3 | 120.0 | NaN | NaN | 186.0 | 8.8 | NaN | NaN | 1.9 | NaN | NaN | NaN | 292.0 | NaN | 42.7 | 4.0 | NaN | NaN | NaN | 7.7 | 32.3 | 19.6 | 91.9 | 35.2 | 4.65 | 16.0 | NaN | 0.3 | 21.0 | 14.0 | 9.7 | NaN | NaN | 3.0 | 5.0 | NaN | 2.0 | NaN | 0 | 13 | 46.0 | 3 | 15 | 0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 42.276914 |
| 19316 | 14 | 16 | 2 | 5 | 205 | 1 | 80.7 | 35.15 | 2880.0 | 103.0 | 66.0 | 83.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 24.0 | 141.0 | 0.64 | NaN | NaN | NaN | NaN | NaN | NaN | 4.1 | 59.0 | NaN | NaN | 124.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 2.8 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 8.6 | 3.3 | NaN | NaN | NaN | NaN | 4.0 | NaN | 0 | 13 | 79.0 | 3 | 16 | 7 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 67.030720 |
| 70451 | 14 | 17 | 4 | 5 | 1030 | 2 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 2 | 54 | NaN | 5 | 19 | 58 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 59960 | 42 | 16 | 2 | 17 | 208 | 0 | 68.3 | 31.17 | 3184.0 | 126.0 | 76.0 | 88.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 139.0 | 33.0 | 82.0 | 141.0 | 4.3 | 14.5 | NaN | 29.0 | 137.0 | 1.63 | 55.0 | 115.0 | 10.0 | 68.0 | 16.0 | 0.0 | 4.4 | 43.0 | 3.030 | NaN | 110.0 | 6.1 | NaN | 14.00 | 1.4 | NaN | NaN | NaN | 204.0 | NaN | 43.0 | 4.2 | NaN | NaN | NaN | 8.3 | 26.6 | 14.1 | 79.3 | 33.6 | 5.43 | 18.0 | NaN | 0.9 | 16.0 | 20.0 | 9.7 | 2.9 | NaN | NaN | 1.0 | 4.0 | NaN | 3.0 | 1 | 13 | 67.0 | 1 | 3 | 28 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 67.582759 |
| 28666 | 31 | 2 | 2 | 13 | 635 | 0 | 72.3 | 33.20 | 4480.0 | NaN | NaN | NaN | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 4.9 | 11.8 | NaN | 31.0 | 140.0 | 1.53 | NaN | NaN | NaN | NaN | NaN | NaN | 4.1 | 45.0 | NaN | NaN | 144.0 | 6.8 | NaN | 13.79 | NaN | NaN | NaN | NaN | 163.0 | NaN | 35.4 | 3.7 | 25.90 | NaN | NaN | 8.4 | 29.9 | NaN | 89.6 | 33.3 | 3.95 | NaN | NaN | NaN | NaN | NaN | 8.4 | NaN | NaN | NaN | NaN | NaN | 7.0 | NaN | 1 | 13 | 71.0 | 3 | 3 | 10 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 83.637180 |
| 78623 | 26 | 16 | 2 | 11 | 396 | 1 | 77.2 | NaN | NaN | 152.0 | 78.0 | 72.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 11.3 | 9.4 | NaN | 24.0 | 134.0 | 0.47 | 60.0 | NaN | 1.2 | 81.1 | 7.0 | 0.4 | 4.1 | 59.0 | 3.782 | NaN | 84.0 | NaN | NaN | 6.00 | 2.1 | 23.0 | 523.0 | 2359.0 | 355.0 | 44.0 | 30.5 | 1.9 | 6.80 | 2.0 | 2.5 | 6.8 | 25.0 | 18.8 | 84.6 | 33.0 | 3.45 | 14.0 | NaN | NaN | NaN | NaN | 8.4 | 2.9 | NaN | 1.0 | NaN | NaN | 1.0 | NaN | 0 | 13 | 77.0 | 3 | 16 | 3 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.012928 |
| 15195 | 37 | 16 | 2 | 15 | 836 | 1 | 60.8 | 33.27 | 2864.0 | 124.0 | 80.0 | 71.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 11.2 | 14.3 | NaN | 25.0 | 143.0 | 0.89 | 55.0 | NaN | 1.7 | 79.0 | 4.0 | 0.3 | 3.7 | 70.0 | NaN | NaN | 157.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 297.0 | NaN | 43.5 | 3.8 | NaN | NaN | NaN | 8.1 | 29.1 | 13.7 | 88.4 | 32.9 | 4.93 | 15.0 | NaN | 0.2 | 29.0 | 17.0 | 9.5 | NaN | 3.0 | NaN | 1.0 | 2.0 | 5.0 | 1.0 | 0 | 13 | 60.0 | 1 | 3 | 30 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 89.445526 |
| 63808 | 42 | 16 | 2 | 17 | 198 | 1 | 74.1 | 24.89 | 2320.0 | 118.0 | 82.0 | 87.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 136.0 | 61.0 | 53.0 | 108.0 | 6.7 | 14.3 | NaN | 24.0 | 140.0 | 1.14 | 45.0 | NaN | 1.0 | 58.0 | 8.0 | 1.0 | 4.1 | 47.0 | 1.370 | NaN | 97.0 | 5.8 | NaN | 45.00 | NaN | NaN | 940.0 | NaN | 188.0 | 37.0 | 43.1 | 4.3 | NaN | 3.0 | 3.0 | 7.4 | 32.0 | 13.6 | 96.4 | 33.2 | 4.47 | 32.0 | NaN | 0.6 | 33.0 | 38.0 | 9.6 | NaN | 1.0 | NaN | 1.0 | 5.0 | 3.0 | NaN | 0 | 13 | 74.0 | 1 | 3 | 28 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 64.393686 |
| 3116 | 39 | 16 | 2 | 16 | 1347 | 0 | 65.6 | 32.86 | 3664.0 | 117.0 | 78.0 | 77.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 181.0 | 30.0 | 115.0 | 180.0 | 12.4 | 13.2 | 5.0 | 25.0 | 135.0 | 1.00 | 50.0 | NaN | NaN | NaN | NaN | NaN | 4.2 | 60.0 | 2.149 | 1.35 | 158.0 | 8.4 | NaN | NaN | 2.1 | NaN | NaN | NaN | 271.0 | NaN | 38.6 | 2.6 | NaN | NaN | NaN | 10.1 | 31.2 | 16.4 | 91.0 | 34.3 | 4.24 | NaN | NaN | 12.1 | 63.0 | 158.0 | 9.7 | 3.5 | NaN | NaN | NaN | 5.0 | 1.0 | NaN | 1 | 13 | 65.0 | 2 | 3 | 34 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 74.978456 |
| 77992 | 21 | 16 | 2 | 8 | 1015 | 0 | 34.5 | 31.14 | 3776.0 | 165.0 | 103.0 | 98.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 9.7 | 13.8 | NaN | 26.0 | 140.0 | 0.92 | NaN | NaN | 2.5 | 50.1 | 7.7 | 1.3 | 4.6 | 59.0 | NaN | NaN | 110.0 | NaN | NaN | NaN | 2.0 | NaN | NaN | NaN | 233.0 | NaN | 40.7 | 4.0 | NaN | NaN | NaN | 8.6 | 31.9 | 13.0 | 93.9 | 33.9 | 4.33 | 38.4 | NaN | 0.6 | 25.0 | 10.0 | 8.1 | 3.2 | NaN | 2.0 | 6.0 | NaN | NaN | NaN | 1 | 13 | 36.0 | 4 | 3 | 30 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 62.224959 |
| 66472 | 26 | 16 | 2 | 11 | 1095 | 0 | 77.1 | 26.50 | 2707.0 | 122.0 | 78.0 | 64.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 136.0 | 45.0 | 69.0 | 109.0 | 6.1 | 14.6 | NaN | 28.0 | 140.0 | 1.18 | NaN | NaN | 1.0 | 67.0 | 10.0 | 1.0 | 4.9 | 59.0 | 3.360 | NaN | 88.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 165.0 | NaN | 45.4 | 4.1 | NaN | NaN | NaN | 10.3 | 29.2 | 14.1 | 90.9 | 32.2 | 5.00 | 22.0 | NaN | 0.5 | 12.0 | 19.0 | 9.2 | NaN | NaN | NaN | NaN | NaN | 4.0 | NaN | 2 | 54 | NaN | 5 | 19 | 58 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 79.080879 |
| 10105 | 21 | 17 | 4 | 8 | 1046 | 2 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1 | 13 | 25.0 | 1 | 3 | 30 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 62.224959 |
# Create index for categorical variables
predictors = x_train_cat
categorical_var = np.where(predictors.dtypes != np.float)[0]
print('\nCategorical Variables indices : ',categorical_var)
Categorical Variables indices : [ 0 1 2 3 4 5 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 171 172 174 175 176]
# Importing CatBoostClassifier, Pool, cv from CatBoost
from catboost import CatBoostClassifier, Pool, cv
# Setting parameters and implementing Logloss in CatBoostClassifier
cat_boost_model = CatBoostClassifier(
loss_function = 'Logloss',
random_seed=42,
iterations = 10,
learning_rate = 0.03,
early_stopping_rounds = 10,
#l2_leaf_reg = ???
depth = 3
)
# Fitting CatBoost model
cat_boost_model.fit(
x_train_cat, y_train
,cat_features=categorical_var,
eval_set=(x_val_cat, y_val)
, plot = True
)
0: learn: 0.6775012 test: 0.6776091 best: 0.6776091 (0) total: 280ms remaining: 2.52s 1: learn: 0.6631555 test: 0.6634204 best: 0.6634204 (1) total: 424ms remaining: 1.69s 2: learn: 0.6493453 test: 0.6498030 best: 0.6498030 (2) total: 665ms remaining: 1.55s 3: learn: 0.6369213 test: 0.6374466 best: 0.6374466 (3) total: 825ms remaining: 1.24s 4: learn: 0.6256758 test: 0.6264573 best: 0.6264573 (4) total: 1.12s remaining: 1.12s 5: learn: 0.6137253 test: 0.6147936 best: 0.6147936 (5) total: 1.23s remaining: 822ms 6: learn: 0.6028308 test: 0.6038549 best: 0.6038549 (6) total: 1.42s remaining: 607ms 7: learn: 0.5933029 test: 0.5945219 best: 0.5945219 (7) total: 1.55s remaining: 389ms 8: learn: 0.5842418 test: 0.5857013 best: 0.5857013 (8) total: 1.7s remaining: 188ms 9: learn: 0.5761256 test: 0.5778106 best: 0.5778106 (9) total: 1.81s remaining: 0us bestTest = 0.5778106395 bestIteration = 9
<catboost.core.CatBoostClassifier at 0x124bcd518>
# CatBoost Probabilities
catboost_probs_train = cat_boost_model.predict_proba(x_train_cat)
catboost_probs = cat_boost_model.predict_proba(x_test_cat)
import sklearn.metrics as metrics
catboost_probs_df_train = pd.DataFrame(catboost_probs_train)
catboost_probs_df_train = catboost_probs_df_train.add_prefix('cat')
catboost_probs_df = pd.DataFrame(catboost_probs)
catboost_probs_df = catboost_probs_df.add_prefix('cat')
fprc, tprc, thresholds = metrics.roc_curve(y_train, catboost_probs_df_train['cat1'])
metrics.auc(fprc, tprc)
0.7645816237012635
print('CatBoost Train AUC:', metrics.auc(fprc, tprc))
CatBoost Train AUC: 0.7645816237012635
fprc, tprc, thresholds = metrics.roc_curve(y_test, catboost_probs_df['cat1'])
metrics.auc(fprc, tprc)
0.7586551484312447
print('CatBoost Test AUC:', metrics.auc(fprc, tprc))
CatBoost Test AUC: 0.7586551484312447
# Importing XGBoost
import xgboost as xgb
# Checking sample data from x_train
x_train.head()
| SCHED_SURG_AREA | RACE | ETHNIC_GROUP | SCHED_HOSPITAL | SCHED_SURG_PROC_CD | FEMALE | AGE_ON_CONTACT_DATE | BMI | WEIGHT | BP_SYSTOLIC | BP_DIASTOLIC | PULSE | PCPVISIT | METFORMIN_FLAG | OPIOIDS_FLAG | ALPHA_BLOCKERS | CENTRAL_ANTAGONISTS | RENIN | BETA_BLOCKERS | ACE_INHIB | ARB | ALDOSTERONE_BLOCKERS | VASODIALATORS | DIURETICS | CALCIUM_BLOCKERS | STATINS | INSULIN_MEDS | ASPIRIN | WARFARIN | DOACS | PRETERM_17P | MEDROL | PREDNISONE | INHALED_STEROID_WITH_LABA | INHALED_STEROID_WITHOUT_LABA | INHALED_STEROIDS | ASTHMA_BIOLOGICS | SHORT_ACTING_BRONCHO_DIALATORS | TNF_INHIBITORS | IMMUNOMODULATORS | AMINOSALICYLATES | CORTICOSTEROIDS | ARNI | ALLOPURINOL | SEIZURE | MUSCLERELAXANT | DIGOXIN | INOTROPES | ANTI_ARRHYTHMIC | ANTIPLATELET | SULFONYLUREA | GLP_1_AGONIST | THIAZOLIDINEDIONE | SGLT2_INHIBITOR | DPP4_INHIBITOR | ALPHA_GLUCOSIDASE_INHIBITOR | AMYLINOMIMETIC | RAPID_ACTING_INSULIN | SHORT_ACTING_INSULIN | INTERMEDIATE_ACTING_INSULIN | LONG_ACTING_INSULIN | MINOCYCLINE | DOXYCYCLINE | MELATONIN | METHAZOLAMIDE | HYDROXYCHLOROQUINE | ITTC | DMARDS | OBESE_HST | MORBIDOBESE_HST | PH_HST | AFIB_HST | COPD_HST | CHF_HST | DIAB_HST | CAD_HST | OSTEO_HST | HTN_HST | CANCER_HST | LUNG_CANCER_HST | OVARIAN_CANCER_HST | HEAD_NECK_CANCER_HST | BREAST_CANCER_HST | ASTHMA_HST | GERD_HST | FIBROMYALGIA_HST | DEPRESSION_HST | PSORIATIC_ARTHRITIS_HST | RHEUM_ARTHRITIS_HST | LUPUS_HST | VTVF_HST | STROKE_HST | VASCULARDISEASE_HST | LOWBACKPAIN_HST | DVT_HST | PE_HST | HYPOTHYROIDISM_HST | ADRENAL_INSUFFICIENCY_HST | INFERTILITY_HST | CKD_HST | ESRD_HST | OBS_SLEEPAPNEA_HST | CARDIAC_ARREST_HST | HEMO_STROKE_HST | MAJOR_BLEED_HST | MACULAR_DEGEN_HST | ANXIETY_HST | HYPERLIPIDEMIA_HST | HIV_HST | ALZHEIMER_HST | COLORECTAL_CANCER_HST | ENDOMETRIAL_CANCER_HST | GLAUCOMA_HST | HIP_PELVIC_FRACTURE_HST | BENIGN_PROSTATIC_HYPERPLASIA_HST | CIRRHOSIS_HST | CIRRHOSIS_HST_1 | CHOLESTEROL_CLOSEST | HDL_CLOSEST | LDL_CLOSEST | TRIG_CLOSEST | WBC_CLOSEST | HGB_CLOSEST | URIC_ACID_CLOSEST | HCO3_CLOSEST | SODIUM_CLOSEST | CREATININE_CLOSEST | EF_CLOSEST | FEV1_CLOSEST | EOS_CLOSEST | NEUTRO_CLOSEST | MONO_CLOSEST | BASOPHIL_CLOSEST | K_CLOSEST | EGFR_CLOSEST | TSH_CLOSEST | T4_CLOSEST | GLUCOSE_CLOSEST | HBA1C_CLOSEST | ESR_CLOSEST | VITAMIN_D_CLOSEST | MAGNESIUM_CLOSEST | FOLICAC_CLOSEST | VIT_B12_CLOSEST | BNP_CLOSEST | PLATELET_CLOSEST | PA_PRESSURE_CLOSEST | HEMATOCRIT_CLOSEST | ALBUMIN_CLOSEST | PREALBUMIN_CLOSEST | MR_CLOSEST | TR_CLOSEST | MEANPLATELETVOL_CLOSEST | MCH_CLOSEST | RDW_CLOSEST | MCV_CLOSEST | MCHC_CLOSEST | RBC_CLOSEST | LYMPHOCYTE_CLOSEST | CA125_CLOSEST | BILIRUBIN_CLOSEST | ALT_CLOSEST | AST_CLOSEST | CA_CLOSEST | PHOSPHORUS_CLOSEST | URINEPROTEIN_CLOSEST | TOTALPREVIOUSHOSPVISITS | TOTALPREVIOUSEDVISITS | TOTALPREVIOUSPCPVISITS | PREVIOUSSPECIALTYVISIT | PREVIOUSURGENTCAREVISIT | CAV_REC_SEX | CAV_REC_LANG | CAV_REC_AGE | CAV_REC_IPOP | CAV_REC_PRIORITY_CODE | CAV_REC_DISP_CODE | UREA_NITROGEN_MAX_1 | UREA_NITROGEN_MIN_1 | CALCIUM_MAX_1 | CALCIUM_MIN_1 | IRON_MAX_1 | IRON_MIN_1 | GLUCOSE_MAX_1 | GLUCOSE_MIN_1 | HGB_MAX_1 | HGB_MIN_1 | HEMATOCRIT_MAX_1 | HEMATOCRIT_MIN_1 | CHLORIDE_MAX_1 | CHLORIDE_MIN_1 | SODIUM_MAX_1 | SODIUM_MIN_1 | CREATININE_MAX_1 | CREATININE_MIN_1 | CARBON_DIOXIDE_MAX_1 | CARBON_DIOXIDE_MIN_1 | RBC_MAX_1 | RBC_MIN_1 | MCV_MAX_1 | MCV_MIN_1 | MCH_MAX_1 | MCH_MIN_1 | MCHC_MAX_1 | MCHC_MIN_1 | ANION_GAP_MAX_1 | ANION_GAP_MIN_1 | PLATELETS_MAX_1 | PLATELETS_MIN_1 | WBC_MAX_1 | WBC_MIN_1 | MEAN_PLATELET_VOLUME_MAX_1 | MEAN_PLATELET_VOLUME_MIN_1 | EGFR_MAX_1 | EGFR_MIN_1 | RDW_MAX_1 | RDW_MIN_1 | BASOPHILS_MAX_1 | BASOPHILS_MIN_1 | NEUTROPHILS_MAX_1 | NEUTROPHILS_MIN_1 | LYMPHOCYTES_MAX_1 | LYMPHOCYTES_MIN_1 | MONOCYTES_MAX_1 | MONOCYTES_MIN_1 | EOSINOPHILS_MAX_1 | EOSINOPHILS_MIN_1 | MAGNESIUM_MAX_1 | MAGNESIUM_MIN_1 | PHOSPHORUS_MAX_1 | PHOSPHORUS_MIN_1 | INR_MAX_1 | INR_MIN_1 | ALBUMIN_MAX_1 | ALBUMIN_MIN_1 | TOTAL_BILIRUBIN_MAX_1 | TOTAL_BILIRUBIN_MIN_1 | AST_MAX_1 | AST_MIN_1 | ALT_MAX_1 | ALT_MIN_1 | ALKALINE_PHOSPHATASE_MAX_1 | ALKALINE_PHOSPHATASE_MIN_1 | TOTAL_PROTEIN_MAX_1 | TOTAL_PROTEIN_MIN_1 | BUN_CREATININE_RATIO_MAX_1 | ACTIVATED_PTT_MAX_1 | BUN_CREATININE_RATIO_MIN_1 | ACTIVATED_PTT_MIN_1 | TROPONIN_I_MAX_1 | TROPONIN_I_MIN_1 | SPECIFIC_GRAVITY_URINE_MAX_1 | SPECIFIC_GRAVITY_URINE_MIN_1 | PROTEIN_URINE_MAX_1 | PROTEIN_URINE_MIN_1 | PH_URINE_MAX_1 | PH_URINE_MIN_1 | KETONES_URINE_MAX_1 | KETONES_URINE_MIN_1 | URINE_NITRITE_MAX_1 | URINE_NITRITE_MIN_1 | LEUKOCYTE_ESTERASE_MAX_1 | LEUKOCYTE_ESTERASE_MIN_1 | BLOOD_URINE_MAX_1 | BLOOD_URINE_MIN_1 | BILIRUBIN_URINE_MAX_1 | BILIRUBIN_URINE_MIN_1 | UROBILINOGEN_URINE_MAX_1 | UROBILINOGEN_URINE_MIN_1 | WHITE_BLOOD_CELLS_URINE_MAX_1 | WHITE_BLOOD_CELLS_URINE_MIN_1 | RED_BLOOD_CELLS_URINE_MAX_1 | RED_BLOOD_CELLS_URINE_MIN_1 | CALCULATED_OSMOLALITY_MAX_1 | CALCULATED_OSMOLALITY_MIN_1 | DIRECT_BILIRUBIN_MAX_1 | DIRECT_BILIRUBIN_MIN_1 | LACTATE_BLOOD_MAX_1 | LACTATE_BLOOD_MIN_1 | BACTERIA_MAX_1 | BACTERIA_MIN_1 | EPITHELIAL_CELLS_MAX_1 | EPITHELIAL_CELLS_MIN_1 | AG_RATIO_MAX_1 | AG_RATIO_MIN_1 | PCO2_ARTERIAL_MAX_1 | PCO2_ARTERIAL_MIN_1 | ADI_2015 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 36116 | 19 | 2 | 2 | 8 | 1404 | 1 | 63.1 | 16.47 | 1488.0 | 158.0 | 90.0 | 115.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 2.7 | 9.4 | NaN | 26.1 | 137.0 | 0.70 | NaN | NaN | NaN | NaN | NaN | NaN | 4.3 | 60.0 | NaN | NaN | 109.0 | NaN | NaN | NaN | 2.0 | NaN | NaN | NaN | 289.0 | NaN | 30.9 | 4.0 | NaN | NaN | NaN | 8.7 | 20.4 | 25.5 | 67.0 | 30.4 | 4.61 | NaN | NaN | 0.4 | 32.0 | 56.0 | 10.9 | 3.7 | 1.0 | 1.0 | NaN | NaN | 2.0 | NaN | 0 | 13 | 63.0 | 3 | 3 | 14 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 79.080879 |
| 13231 | 29 | 17 | 4 | 12 | 1015 | 2 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.0 | NaN | NaN | NaN | 1 | 13 | 75.0 | 1 | 3 | 30 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 80.571579 |
| 56836 | 29 | 16 | 2 | 12 | 825 | 1 | 74.7 | 31.01 | 3360.0 | 110.0 | 54.0 | 99.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 110.0 | 24.0 | 45.0 | 203.0 | 4.6 | 10.0 | NaN | 25.0 | 138.0 | 2.01 | 60.0 | NaN | 2.5 | 65.1 | 8.2 | 0.4 | 4.7 | 24.0 | 2.08 | NaN | 177.0 | 8.2 | NaN | 18.0 | 2.0 | 20.0 | 1710.0 | NaN | 84.0 | 37.0 | 30.1 | 3.4 | 5.96 | 2.0 | 1.0 | 9.1 | 30.2 | 15.8 | 90.9 | 33.3 | 3.31 | 23.8 | NaN | 0.4 | 21.0 | 37.0 | 9.1 | 2.7 | 3.0 | 4.0 | 5.0 | 19.0 | 23.0 | NaN | 0 | 13 | 74.0 | 1 | 3 | 30 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 80.571579 |
| 61971 | 35 | 17 | 4 | 14 | 673 | 2 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1 | 13 | 43.0 | 2 | 15 | 15 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 50.716464 |
| 1532 | 19 | 2 | 2 | 8 | 1336 | 0 | 75.3 | 37.84 | 4160.0 | 135.0 | 90.0 | 86.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | 6.2 | 11.9 | NaN | 29.0 | 145.0 | 1.21 | NaN | NaN | 3.9 | 66.4 | 10.4 | 0.2 | 3.9 | 58.0 | NaN | NaN | 92.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 146.0 | NaN | 36.9 | 3.1 | NaN | NaN | NaN | 8.5 | 28.0 | 13.4 | 84.5 | 33.1 | 4.37 | 19.1 | NaN | 0.7 | 20.0 | 18.0 | 8.6 | NaN | NaN | NaN | NaN | NaN | 6.0 | NaN | 1 | 13 | 74.0 | 4 | 3 | 30 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 62.224959 |
dtrain = xgb.DMatrix(data = x_train, label = y_train)
dval = xgb.DMatrix(data = x_val, label = y_val)
dtest = xgb.DMatrix(data = x_test, label = y_test)
# Manual tuning of Hyperparameters
param = {'max_depth':5,
'eta': 0.30,
'silent':1,
'objective':'binary:logistic',
'eval_metric': 'auc'
,'scale_pos_weight' : 1
,'maximize' : 'TRUE'
,'n_jobs' : -1,
'learning_rate':0.01,
'n_estimators':100,
'min_child_weight':1,
'gamma':0,
'subsample':0.8,
'colsample_bytree':0.8,
'nthread':4,
'seed':27
}
# Specify validations set to watch performance
watchlist = [(dtrain, 'train'), (dval, 'eval')]
num_round = 100 # This is another hyperparameter of sorts
bst = xgb.train(param, dtrain, num_round, watchlist, early_stopping_rounds = 10)
[0] train-auc:0.776129 eval-auc:0.763516 Multiple eval metrics have been passed: 'eval-auc' will be used for early stopping. Will train until eval-auc hasn't improved in 10 rounds. [1] train-auc:0.789714 eval-auc:0.774393 [2] train-auc:0.792951 eval-auc:0.777735 [3] train-auc:0.795481 eval-auc:0.780521 [4] train-auc:0.796489 eval-auc:0.782233 [5] train-auc:0.796962 eval-auc:0.783268 [6] train-auc:0.797464 eval-auc:0.783422 [7] train-auc:0.798131 eval-auc:0.783883 [8] train-auc:0.803143 eval-auc:0.789052 [9] train-auc:0.80542 eval-auc:0.790752 [10] train-auc:0.805598 eval-auc:0.790337 [11] train-auc:0.805459 eval-auc:0.789826 [12] train-auc:0.805373 eval-auc:0.789763 [13] train-auc:0.805906 eval-auc:0.790582 [14] train-auc:0.806623 eval-auc:0.791464 [15] train-auc:0.806462 eval-auc:0.791361 [16] train-auc:0.807063 eval-auc:0.791942 [17] train-auc:0.807349 eval-auc:0.791892 [18] train-auc:0.8072 eval-auc:0.79153 [19] train-auc:0.807311 eval-auc:0.791737 [20] train-auc:0.807328 eval-auc:0.791827 [21] train-auc:0.807482 eval-auc:0.792242 [22] train-auc:0.807977 eval-auc:0.79253 [23] train-auc:0.807762 eval-auc:0.792232 [24] train-auc:0.807749 eval-auc:0.792105 [25] train-auc:0.807771 eval-auc:0.7922 [26] train-auc:0.808576 eval-auc:0.793082 [27] train-auc:0.80872 eval-auc:0.793098 [28] train-auc:0.808838 eval-auc:0.793356 [29] train-auc:0.809322 eval-auc:0.793855 [30] train-auc:0.809186 eval-auc:0.793565 [31] train-auc:0.809081 eval-auc:0.793465 [32] train-auc:0.809195 eval-auc:0.793632 [33] train-auc:0.809146 eval-auc:0.793597 [34] train-auc:0.809175 eval-auc:0.793566 [35] train-auc:0.809113 eval-auc:0.793395 [36] train-auc:0.809338 eval-auc:0.793288 [37] train-auc:0.809386 eval-auc:0.793291 [38] train-auc:0.809281 eval-auc:0.793159 [39] train-auc:0.80917 eval-auc:0.792939 Stopping. Best iteration: [29] train-auc:0.809322 eval-auc:0.793855
# Importing Hyperopt
import hyperopt as hp
import lightgbm as lgb
from hyperopt import Trials,fmin,STATUS_OK
/Users/piumallick/anaconda3/lib/python3.7/site-packages/lightgbm/__init__.py:48: UserWarning: Starting from version 2.2.1, the library file in distribution wheels for macOS is built by the Apple Clang (Xcode_8.3.3) compiler. This means that in case of installing LightGBM from PyPI via the ``pip install lightgbm`` command, you don't need to install the gcc compiler anymore. Instead of that, you need to install the OpenMP library, which is required for running LightGBM on the system with the Apple Clang compiler. You can install the OpenMP library by the following command: ``brew install libomp``. "You can install the OpenMP library by the following command: ``brew install libomp``.", UserWarning)
dtrain = xgb.DMatrix(data = x_train, label = y_train)
dval = xgb.DMatrix(data = x_val, label = y_val)
dtest = xgb.DMatrix(data = x_test, label = y_test)
# Sets the space to search over and the prior probabilities over the search space
xgb_space = {
'booster': hp.hp.choice('booster', ['gbtree']),
'eta': hp.hp.loguniform('learning_rate', -4, 0),
'max_depth':hp.hp.choice('max_depth', np.arange(10, 300,1, dtype=int)),
'subsample':hp.hp.quniform('subsample',0.5,1.0,0.05),
'colsample_bytree':hp.hp.quniform('colsample_bytree',0.5,1.0,0.05),
'min_child_weight':hp.hp.quniform('min_child_weight', 100, 1000,100),
'lambda': hp.hp.uniform('reg_alpha', 0.0, 1000.0),
'alpha': hp.hp.uniform('reg_lambda', 0.0, 1000.0),
'gamma': hp.hp.uniform('reg_gamma', 0.0, 1000.0),
'scale_pos_weight': hp.hp.uniform('scale_pos_weight', 1.0, 10.0),
'eval_metric' : hp.hp.choice('eval_metric', ['auc']),
'n_thread': hp.hp.choice('n_thread', [-1]),
'verbose' : hp.hp.choice('verbose', [-1]),
'maximize' : hp.hp.choice('maximize', ['TRUE'])
}
def objective_m(params, n_folds=5):
model = xgb.cv(params = params,
dtrain = dtrain,
num_boost_round = 10,
early_stopping_rounds = 10,
nfold = n_folds)
# Returns the best average loss on validation set
loss = 1 - max(model['test-auc-mean'])
return loss
bayes_trials = Trials()
MAX_EVALS = 100 # this controls the runtime
xgb_best_m = fmin(fn = objective_m, space = xgb_space, algo = hp.tpe.suggest, max_evals = MAX_EVALS, trials = bayes_trials)
100%|██████████| 100/100 [50:53<00:00, 30.54s/trial, best loss: 0.18500700000000003]
# XGBoost Best Parameters
xgb_best_m
{'booster': 0,
'colsample_bytree': 0.6000000000000001,
'eval_metric': 0,
'learning_rate': 0.28957411872608396,
'max_depth': 148,
'maximize': 0,
'min_child_weight': 200.0,
'n_thread': 0,
'reg_alpha': 566.0477313007634,
'reg_gamma': 6.212005945800067,
'reg_lambda': 37.57823272056038,
'scale_pos_weight': 9.941822730350838,
'subsample': 1.0,
'verbose': 0}
# By HyperOpt -- Best Result
param = {'booster': 'gbtree',
'colsample_bytree': 0.95,
'eval_metric': 'auc',
'objective':'binary:logistic',
'learning_rate': 0.32,
'max_depth': 152,
'maximize': 0,
'min_child_weight': 700.0,
'n_thread': 0,
'alpha': 105,
'lambda': 140,
'scale_pos_weight': 7,
'subsample': 0.65,
'verbose': 0}
# Specify validations set to watch performance
watchlist = [(dtrain, 'train'), (dval, 'eval')]
num_round = 100 #This is another hyperparameter of sorts
bst = xgb.train(param, dtrain, num_round, watchlist, early_stopping_rounds = 10)
[0] train-auc:0.750247 eval-auc:0.734134 Multiple eval metrics have been passed: 'eval-auc' will be used for early stopping. Will train until eval-auc hasn't improved in 10 rounds. [1] train-auc:0.768602 eval-auc:0.75546 [2] train-auc:0.777298 eval-auc:0.764766 [3] train-auc:0.780482 eval-auc:0.768677 [4] train-auc:0.788189 eval-auc:0.774307 [5] train-auc:0.798293 eval-auc:0.78277 [6] train-auc:0.80188 eval-auc:0.786236 [7] train-auc:0.806475 eval-auc:0.790884 [8] train-auc:0.809088 eval-auc:0.79414 [9] train-auc:0.812687 eval-auc:0.797245 [10] train-auc:0.819248 eval-auc:0.804344 [11] train-auc:0.821116 eval-auc:0.806352 [12] train-auc:0.822314 eval-auc:0.807379 [13] train-auc:0.823275 eval-auc:0.807556 [14] train-auc:0.823661 eval-auc:0.808075 [15] train-auc:0.824568 eval-auc:0.8087 [16] train-auc:0.826794 eval-auc:0.810764 [17] train-auc:0.827364 eval-auc:0.811007 [18] train-auc:0.828002 eval-auc:0.811441 [19] train-auc:0.830459 eval-auc:0.813992 [20] train-auc:0.831098 eval-auc:0.814504 [21] train-auc:0.831525 eval-auc:0.814437 [22] train-auc:0.83211 eval-auc:0.814736 [23] train-auc:0.832457 eval-auc:0.814922 [24] train-auc:0.832882 eval-auc:0.815047 [25] train-auc:0.833309 eval-auc:0.815069 [26] train-auc:0.833657 eval-auc:0.815326 [27] train-auc:0.834245 eval-auc:0.816033 [28] train-auc:0.835444 eval-auc:0.817141 [29] train-auc:0.835672 eval-auc:0.817445 [30] train-auc:0.836163 eval-auc:0.817744 [31] train-auc:0.836563 eval-auc:0.817911 [32] train-auc:0.836909 eval-auc:0.818021 [33] train-auc:0.837407 eval-auc:0.818182 [34] train-auc:0.837786 eval-auc:0.818375 [35] train-auc:0.83805 eval-auc:0.818371 [36] train-auc:0.838208 eval-auc:0.818598 [37] train-auc:0.838603 eval-auc:0.818668 [38] train-auc:0.839038 eval-auc:0.818943 [39] train-auc:0.839205 eval-auc:0.818863 [40] train-auc:0.839533 eval-auc:0.818978 [41] train-auc:0.839833 eval-auc:0.819102 [42] train-auc:0.840136 eval-auc:0.819068 [43] train-auc:0.840643 eval-auc:0.819963 [44] train-auc:0.840896 eval-auc:0.820288 [45] train-auc:0.841143 eval-auc:0.820282 [46] train-auc:0.841301 eval-auc:0.820088 [47] train-auc:0.841508 eval-auc:0.820327 [48] train-auc:0.841891 eval-auc:0.820483 [49] train-auc:0.842264 eval-auc:0.820688 [50] train-auc:0.842753 eval-auc:0.821047 [51] train-auc:0.843012 eval-auc:0.821326 [52] train-auc:0.843475 eval-auc:0.821809 [53] train-auc:0.843647 eval-auc:0.821809 [54] train-auc:0.843993 eval-auc:0.821965 [55] train-auc:0.844328 eval-auc:0.822314 [56] train-auc:0.844767 eval-auc:0.822619 [57] train-auc:0.844943 eval-auc:0.822568 [58] train-auc:0.84506 eval-auc:0.8227 [59] train-auc:0.845432 eval-auc:0.823101 [60] train-auc:0.846004 eval-auc:0.823802 [61] train-auc:0.8461 eval-auc:0.823981 [62] train-auc:0.846428 eval-auc:0.824154 [63] train-auc:0.846714 eval-auc:0.824383 [64] train-auc:0.84694 eval-auc:0.82453 [65] train-auc:0.847183 eval-auc:0.824576 [66] train-auc:0.847405 eval-auc:0.824686 [67] train-auc:0.847496 eval-auc:0.824805 [68] train-auc:0.847659 eval-auc:0.824766 [69] train-auc:0.84776 eval-auc:0.824636 [70] train-auc:0.847883 eval-auc:0.824718 [71] train-auc:0.847966 eval-auc:0.824756 [72] train-auc:0.848136 eval-auc:0.82471 [73] train-auc:0.848388 eval-auc:0.824967 [74] train-auc:0.848602 eval-auc:0.825231 [75] train-auc:0.848719 eval-auc:0.82506 [76] train-auc:0.849037 eval-auc:0.82528 [77] train-auc:0.849218 eval-auc:0.825317 [78] train-auc:0.849363 eval-auc:0.825441 [79] train-auc:0.849579 eval-auc:0.825574 [80] train-auc:0.849874 eval-auc:0.825767 [81] train-auc:0.85001 eval-auc:0.825781 [82] train-auc:0.85041 eval-auc:0.825986 [83] train-auc:0.850564 eval-auc:0.826049 [84] train-auc:0.850804 eval-auc:0.826122 [85] train-auc:0.85092 eval-auc:0.826077 [86] train-auc:0.851173 eval-auc:0.826208 [87] train-auc:0.851326 eval-auc:0.826316 [88] train-auc:0.85143 eval-auc:0.826347 [89] train-auc:0.851641 eval-auc:0.826414 [90] train-auc:0.851851 eval-auc:0.826466 [91] train-auc:0.852086 eval-auc:0.826568 [92] train-auc:0.85222 eval-auc:0.826607 [93] train-auc:0.852509 eval-auc:0.826612 [94] train-auc:0.852626 eval-auc:0.826425 [95] train-auc:0.85275 eval-auc:0.826522 [96] train-auc:0.852838 eval-auc:0.826598 [97] train-auc:0.853025 eval-auc:0.826585 [98] train-auc:0.853122 eval-auc:0.826535 [99] train-auc:0.853308 eval-auc:0.826586
# Less Accuracy but minimum difference between Train and Validation
param = {'booster': 'gbtree',
'colsample_bytree': 1.0,
'eval_metric': 'auc',
'objective':'binary:logistic',
'learning_rate': 0.20,
'max_depth': 71,
'maximize': 'TRUE',
'min_child_weight': 500.0,
'n_thread': -1,
'alpha': 913,
'gamma': 3,
'lambda': 25,
'scale_pos_weight': 4,
'subsample': 1.0,
'verbose': -1}
# specify validations set to watch performance
watchlist = [(dtrain, 'train'), (dval, 'eval')]
num_round = 100 # This is another hyperparameter of sorts
bst = xgb.train(param, dtrain, num_round, watchlist, early_stopping_rounds = 10)
[0] train-auc:0.742685 eval-auc:0.733831 Multiple eval metrics have been passed: 'eval-auc' will be used for early stopping. Will train until eval-auc hasn't improved in 10 rounds. [1] train-auc:0.749262 eval-auc:0.741844 [2] train-auc:0.757535 eval-auc:0.749857 [3] train-auc:0.762538 eval-auc:0.755563 [4] train-auc:0.767351 eval-auc:0.757893 [5] train-auc:0.769365 eval-auc:0.759817 [6] train-auc:0.774609 eval-auc:0.76486 [7] train-auc:0.779298 eval-auc:0.769379 [8] train-auc:0.783731 eval-auc:0.773162 [9] train-auc:0.786561 eval-auc:0.7758 [10] train-auc:0.788161 eval-auc:0.777829 [11] train-auc:0.790517 eval-auc:0.779625 [12] train-auc:0.792214 eval-auc:0.780711 [13] train-auc:0.792344 eval-auc:0.780796 [14] train-auc:0.793773 eval-auc:0.782398 [15] train-auc:0.794785 eval-auc:0.783252 [16] train-auc:0.795298 eval-auc:0.783887 [17] train-auc:0.796214 eval-auc:0.784477 [18] train-auc:0.79682 eval-auc:0.784738 [19] train-auc:0.798087 eval-auc:0.785503 [20] train-auc:0.798791 eval-auc:0.786014 [21] train-auc:0.798807 eval-auc:0.786079 [22] train-auc:0.799344 eval-auc:0.786369 [23] train-auc:0.799596 eval-auc:0.786814 [24] train-auc:0.800396 eval-auc:0.787385 [25] train-auc:0.80088 eval-auc:0.787764 [26] train-auc:0.801292 eval-auc:0.78804 [27] train-auc:0.801266 eval-auc:0.788071 [28] train-auc:0.80156 eval-auc:0.788074 [29] train-auc:0.801943 eval-auc:0.788384 [30] train-auc:0.802119 eval-auc:0.788425 [31] train-auc:0.80228 eval-auc:0.788728 [32] train-auc:0.803249 eval-auc:0.789648 [33] train-auc:0.80362 eval-auc:0.789989 [34] train-auc:0.80374 eval-auc:0.790171 [35] train-auc:0.803722 eval-auc:0.790204 [36] train-auc:0.80403 eval-auc:0.790358 [37] train-auc:0.80403 eval-auc:0.790358 [38] train-auc:0.80403 eval-auc:0.790358 [39] train-auc:0.80403 eval-auc:0.790358 [40] train-auc:0.80403 eval-auc:0.790358 [41] train-auc:0.80403 eval-auc:0.790358 [42] train-auc:0.80403 eval-auc:0.790358 [43] train-auc:0.80403 eval-auc:0.790358 [44] train-auc:0.80403 eval-auc:0.790358 [45] train-auc:0.80403 eval-auc:0.790358 [46] train-auc:0.80403 eval-auc:0.790358 Stopping. Best iteration: [36] train-auc:0.80403 eval-auc:0.790358
# Importing Hyperband
import hyperband
from hyperband import HyperbandSearchCV
#Hyperband scores models using scikit-learn:
import sklearn
sklearn.metrics.SCORERS.keys()
dict_keys(['explained_variance', 'r2', 'max_error', 'neg_median_absolute_error', 'neg_mean_absolute_error', 'neg_mean_squared_error', 'neg_mean_squared_log_error', 'neg_root_mean_squared_error', 'neg_mean_poisson_deviance', 'neg_mean_gamma_deviance', 'accuracy', 'roc_auc', 'roc_auc_ovr', 'roc_auc_ovo', 'roc_auc_ovr_weighted', 'roc_auc_ovo_weighted', 'balanced_accuracy', 'average_precision', 'neg_log_loss', 'neg_brier_score', 'adjusted_rand_score', 'homogeneity_score', 'completeness_score', 'v_measure_score', 'mutual_info_score', 'adjusted_mutual_info_score', 'normalized_mutual_info_score', 'fowlkes_mallows_score', 'precision', 'precision_macro', 'precision_micro', 'precision_samples', 'precision_weighted', 'recall', 'recall_macro', 'recall_micro', 'recall_samples', 'recall_weighted', 'f1', 'f1_macro', 'f1_micro', 'f1_samples', 'f1_weighted', 'jaccard', 'jaccard_macro', 'jaccard_micro', 'jaccard_samples', 'jaccard_weighted'])
hb_xgb_model = xgb.XGBClassifier()
xgb_hb_param_dict = {'max_depth' : np.arange(70, 160),
'learning_rate' : np.arange(0.001),
'n_estimators' : np.arange(50, 200),
'objective' : ['binary:logistic'],
#'gamma' : [],
#'min_child_weight' : [],
#'max_delta_step' : [],
#'subsample' : [],
#'colsample_by_tree' : [],
#'colsample_by_level' : [],
#'colsample_by_node' : [],
#'reg_alpha' : [],
#'reg_lambda' : [],
#'scale_pos_weight' : []
}
xgb_search = HyperbandSearchCV(hb_xgb_model, xgb_hb_param_dict, cv=3,
verbose = 1,
max_iter=20,min_iter=5,
scoring='roc_auc')
xgb_search.fit(x_train,y_train)
Starting bracket 1 (out of 2) of hyperband Starting successive halving iteration 1 out of 2. Fitting 3 configurations, with resource_param n_estimators set to 6, and keeping the best 1 configurations. Fitting 3 folds for each of 3 candidates, totalling 9 fits
[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers. [Parallel(n_jobs=1)]: Done 9 out of 9 | elapsed: 2.0min finished /Users/piumallick/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:823: FutureWarning: The parameter 'iid' is deprecated in 0.22 and will be removed in 0.24. "removed in 0.24.", FutureWarning [Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.
Starting successive halving iteration 2 out of 2. Fitting 1 configurations, with resource_param n_estimators set to 20 Fitting 3 folds for each of 1 candidates, totalling 3 fits
[Parallel(n_jobs=1)]: Done 3 out of 3 | elapsed: 2.1min finished /Users/piumallick/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:823: FutureWarning: The parameter 'iid' is deprecated in 0.22 and will be removed in 0.24. "removed in 0.24.", FutureWarning [Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.
Starting bracket 2 (out of 2) of hyperband Starting successive halving iteration 1 out of 1. Fitting 2 configurations, with resource_param n_estimators set to 20 Fitting 3 folds for each of 2 candidates, totalling 6 fits
[Parallel(n_jobs=1)]: Done 6 out of 6 | elapsed: 4.1min finished /Users/piumallick/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:823: FutureWarning: The parameter 'iid' is deprecated in 0.22 and will be removed in 0.24. "removed in 0.24.", FutureWarning
HyperbandSearchCV(cv=3, error_score='raise',
estimator=XGBClassifier(base_score=0.5, booster='gbtree',
colsample_bylevel=1,
colsample_bynode=1,
colsample_bytree=1, gamma=0,
learning_rate=0.1, max_delta_step=0,
max_depth=3, min_child_weight=1,
missing=None, n_estimators=100,
n_jobs=1, nthread=None,
objective='binary:logistic',
random_state=0, reg_alpha=0,
reg_lambda=1...
154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166,
167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179,
180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192,
193, 194, 195, 196, 197, 198, 199]),
'objective': ['binary:logistic']},
pre_dispatch='2*n_jobs', random_state=None, refit=True,
resource_param='n_estimators', return_train_score=False,
scoring='roc_auc', skip_last=0, verbose=1)
xgb_search.best_score_
0.5
# Importing LightGBM
import lightgbm as lgb
# LightGBM Manual Parameter Tuning
lgb_params = {
'boosting_type': 'gbdt',
'objective': 'binary',
'metric': 'auc',
'max_depth' : 3,
'num_leaves' : 51,
'learning_rate': 0.1,
'num_threads' : -1,
'scale_pos_weight' : 1.1,
'early_stopping_round' : 20,
#'top_rate' : 0.6,
#'other_rate' : 0.05,
'lambda_l1' : 20,
'lambda_l2' : 0.09951595323870244
}
lgb_proc_train_rh = lgb.Dataset(x_train, y_train)
lgb_proc_val_rh = lgb.Dataset(x_val, y_val)
gbm_rh = lgb.train(params = lgb_params, train_set = lgb_proc_train_rh,
num_boost_round = 5000, valid_sets = [lgb_proc_val_rh, lgb_proc_train_rh],
valid_names = ['Evaluation', 'Train'])
/Users/piumallick/anaconda3/lib/python3.7/site-packages/lightgbm/engine.py:153: UserWarning: Found `early_stopping_round` in params. Will use it instead of argument
warnings.warn("Found `{}` in params. Will use it instead of argument".format(alias))
[1] Train's auc: 0.746099 Evaluation's auc: 0.737671 Training until validation scores don't improve for 20 rounds [2] Train's auc: 0.759424 Evaluation's auc: 0.752346 [3] Train's auc: 0.760165 Evaluation's auc: 0.752714 [4] Train's auc: 0.765161 Evaluation's auc: 0.759173 [5] Train's auc: 0.764795 Evaluation's auc: 0.758286 [6] Train's auc: 0.766336 Evaluation's auc: 0.758787 [7] Train's auc: 0.768518 Evaluation's auc: 0.760997 [8] Train's auc: 0.773839 Evaluation's auc: 0.765187 [9] Train's auc: 0.776775 Evaluation's auc: 0.767291 [10] Train's auc: 0.779615 Evaluation's auc: 0.769877 [11] Train's auc: 0.785295 Evaluation's auc: 0.775861 [12] Train's auc: 0.787069 Evaluation's auc: 0.776502 [13] Train's auc: 0.788873 Evaluation's auc: 0.778081 [14] Train's auc: 0.790106 Evaluation's auc: 0.779426 [15] Train's auc: 0.792344 Evaluation's auc: 0.781349 [16] Train's auc: 0.794798 Evaluation's auc: 0.783194 [17] Train's auc: 0.795146 Evaluation's auc: 0.783768 [18] Train's auc: 0.796552 Evaluation's auc: 0.785056 [19] Train's auc: 0.797846 Evaluation's auc: 0.785809 [20] Train's auc: 0.798451 Evaluation's auc: 0.785843 [21] Train's auc: 0.799177 Evaluation's auc: 0.786626 [22] Train's auc: 0.799487 Evaluation's auc: 0.786859 [23] Train's auc: 0.800682 Evaluation's auc: 0.787653 [24] Train's auc: 0.801601 Evaluation's auc: 0.788118 [25] Train's auc: 0.802831 Evaluation's auc: 0.789296 [26] Train's auc: 0.803575 Evaluation's auc: 0.789936 [27] Train's auc: 0.805655 Evaluation's auc: 0.792076 [28] Train's auc: 0.806132 Evaluation's auc: 0.792355 [29] Train's auc: 0.806482 Evaluation's auc: 0.792796 [30] Train's auc: 0.807828 Evaluation's auc: 0.794053 [31] Train's auc: 0.808449 Evaluation's auc: 0.794537 [32] Train's auc: 0.80917 Evaluation's auc: 0.795125 [33] Train's auc: 0.811215 Evaluation's auc: 0.797431 [34] Train's auc: 0.811662 Evaluation's auc: 0.797655 [35] Train's auc: 0.812173 Evaluation's auc: 0.798341 [36] Train's auc: 0.812404 Evaluation's auc: 0.798492 [37] Train's auc: 0.812905 Evaluation's auc: 0.798779 [38] Train's auc: 0.8136 Evaluation's auc: 0.799331 [39] Train's auc: 0.814277 Evaluation's auc: 0.800107 [40] Train's auc: 0.814674 Evaluation's auc: 0.800668 [41] Train's auc: 0.81483 Evaluation's auc: 0.800638 [42] Train's auc: 0.815771 Evaluation's auc: 0.801351 [43] Train's auc: 0.816582 Evaluation's auc: 0.801897 [44] Train's auc: 0.816672 Evaluation's auc: 0.801986 [45] Train's auc: 0.817484 Evaluation's auc: 0.802736 [46] Train's auc: 0.817676 Evaluation's auc: 0.802863 [47] Train's auc: 0.819231 Evaluation's auc: 0.804287 [48] Train's auc: 0.819691 Evaluation's auc: 0.804552 [49] Train's auc: 0.820377 Evaluation's auc: 0.805087 [50] Train's auc: 0.820626 Evaluation's auc: 0.805446 [51] Train's auc: 0.82176 Evaluation's auc: 0.806854 [52] Train's auc: 0.822943 Evaluation's auc: 0.80789 [53] Train's auc: 0.823333 Evaluation's auc: 0.808271 [54] Train's auc: 0.823643 Evaluation's auc: 0.808414 [55] Train's auc: 0.824503 Evaluation's auc: 0.809417 [56] Train's auc: 0.825379 Evaluation's auc: 0.810144 [57] Train's auc: 0.825869 Evaluation's auc: 0.810496 [58] Train's auc: 0.826524 Evaluation's auc: 0.811021 [59] Train's auc: 0.826686 Evaluation's auc: 0.81112 [60] Train's auc: 0.827675 Evaluation's auc: 0.812095 [61] Train's auc: 0.827915 Evaluation's auc: 0.812325 [62] Train's auc: 0.828142 Evaluation's auc: 0.812488 [63] Train's auc: 0.828342 Evaluation's auc: 0.812624 [64] Train's auc: 0.828954 Evaluation's auc: 0.813222 [65] Train's auc: 0.829283 Evaluation's auc: 0.813587 [66] Train's auc: 0.829948 Evaluation's auc: 0.814154 [67] Train's auc: 0.830112 Evaluation's auc: 0.814217 [68] Train's auc: 0.830328 Evaluation's auc: 0.814298 [69] Train's auc: 0.830511 Evaluation's auc: 0.814463 [70] Train's auc: 0.830812 Evaluation's auc: 0.814833 [71] Train's auc: 0.831285 Evaluation's auc: 0.815248 [72] Train's auc: 0.831702 Evaluation's auc: 0.815614 [73] Train's auc: 0.832003 Evaluation's auc: 0.815871 [74] Train's auc: 0.832541 Evaluation's auc: 0.816368 [75] Train's auc: 0.83275 Evaluation's auc: 0.81654 [76] Train's auc: 0.832866 Evaluation's auc: 0.816599 [77] Train's auc: 0.833073 Evaluation's auc: 0.816755 [78] Train's auc: 0.833581 Evaluation's auc: 0.817361 [79] Train's auc: 0.833926 Evaluation's auc: 0.817808 [80] Train's auc: 0.834038 Evaluation's auc: 0.817918 [81] Train's auc: 0.834469 Evaluation's auc: 0.818319 [82] Train's auc: 0.834611 Evaluation's auc: 0.818393 [83] Train's auc: 0.834958 Evaluation's auc: 0.818871 [84] Train's auc: 0.83513 Evaluation's auc: 0.81899 [85] Train's auc: 0.835311 Evaluation's auc: 0.819194 [86] Train's auc: 0.835664 Evaluation's auc: 0.819482 [87] Train's auc: 0.835912 Evaluation's auc: 0.819569 [88] Train's auc: 0.836048 Evaluation's auc: 0.81959 [89] Train's auc: 0.836181 Evaluation's auc: 0.819584 [90] Train's auc: 0.836381 Evaluation's auc: 0.819694 [91] Train's auc: 0.836594 Evaluation's auc: 0.819858 [92] Train's auc: 0.8369 Evaluation's auc: 0.820299 [93] Train's auc: 0.837207 Evaluation's auc: 0.8206 [94] Train's auc: 0.837393 Evaluation's auc: 0.820827 [95] Train's auc: 0.837543 Evaluation's auc: 0.82096 [96] Train's auc: 0.837845 Evaluation's auc: 0.821236 [97] Train's auc: 0.837973 Evaluation's auc: 0.821303 [98] Train's auc: 0.838349 Evaluation's auc: 0.821646 [99] Train's auc: 0.838596 Evaluation's auc: 0.82182 [100] Train's auc: 0.838682 Evaluation's auc: 0.821898 [101] Train's auc: 0.838937 Evaluation's auc: 0.822197 [102] Train's auc: 0.839088 Evaluation's auc: 0.822333 [103] Train's auc: 0.839314 Evaluation's auc: 0.822635 [104] Train's auc: 0.839423 Evaluation's auc: 0.822702 [105] Train's auc: 0.839575 Evaluation's auc: 0.822706 [106] Train's auc: 0.83986 Evaluation's auc: 0.822951 [107] Train's auc: 0.840307 Evaluation's auc: 0.823477 [108] Train's auc: 0.840404 Evaluation's auc: 0.823507 [109] Train's auc: 0.840542 Evaluation's auc: 0.823642 [110] Train's auc: 0.840613 Evaluation's auc: 0.82364 [111] Train's auc: 0.8407 Evaluation's auc: 0.823623 [112] Train's auc: 0.840831 Evaluation's auc: 0.823696 [113] Train's auc: 0.840991 Evaluation's auc: 0.823804 [114] Train's auc: 0.841058 Evaluation's auc: 0.823837 [115] Train's auc: 0.841206 Evaluation's auc: 0.823936 [116] Train's auc: 0.841296 Evaluation's auc: 0.824009 [117] Train's auc: 0.841396 Evaluation's auc: 0.824046 [118] Train's auc: 0.841533 Evaluation's auc: 0.824114 [119] Train's auc: 0.841741 Evaluation's auc: 0.824321 [120] Train's auc: 0.841851 Evaluation's auc: 0.824338 [121] Train's auc: 0.842003 Evaluation's auc: 0.824394 [122] Train's auc: 0.842103 Evaluation's auc: 0.824518 [123] Train's auc: 0.842214 Evaluation's auc: 0.824526 [124] Train's auc: 0.84234 Evaluation's auc: 0.82471 [125] Train's auc: 0.842497 Evaluation's auc: 0.824809 [126] Train's auc: 0.842593 Evaluation's auc: 0.824882 [127] Train's auc: 0.842697 Evaluation's auc: 0.824924 [128] Train's auc: 0.842853 Evaluation's auc: 0.825104 [129] Train's auc: 0.84294 Evaluation's auc: 0.825146 [130] Train's auc: 0.843041 Evaluation's auc: 0.825237 [131] Train's auc: 0.843083 Evaluation's auc: 0.825195 [132] Train's auc: 0.843211 Evaluation's auc: 0.825252 [133] Train's auc: 0.84328 Evaluation's auc: 0.825226 [134] Train's auc: 0.8434 Evaluation's auc: 0.825218 [135] Train's auc: 0.843506 Evaluation's auc: 0.825329 [136] Train's auc: 0.843608 Evaluation's auc: 0.825338 [137] Train's auc: 0.843674 Evaluation's auc: 0.82534 [138] Train's auc: 0.843891 Evaluation's auc: 0.825604 [139] Train's auc: 0.84398 Evaluation's auc: 0.825591 [140] Train's auc: 0.844089 Evaluation's auc: 0.825683 [141] Train's auc: 0.844276 Evaluation's auc: 0.825838 [142] Train's auc: 0.844666 Evaluation's auc: 0.826279 [143] Train's auc: 0.844795 Evaluation's auc: 0.826219 [144] Train's auc: 0.844846 Evaluation's auc: 0.8262 [145] Train's auc: 0.844955 Evaluation's auc: 0.826275 [146] Train's auc: 0.845256 Evaluation's auc: 0.826623 [147] Train's auc: 0.845374 Evaluation's auc: 0.826687 [148] Train's auc: 0.845431 Evaluation's auc: 0.826746 [149] Train's auc: 0.845473 Evaluation's auc: 0.826766 [150] Train's auc: 0.845584 Evaluation's auc: 0.826814 [151] Train's auc: 0.845656 Evaluation's auc: 0.826787 [152] Train's auc: 0.845882 Evaluation's auc: 0.827083 [153] Train's auc: 0.845977 Evaluation's auc: 0.827197 [154] Train's auc: 0.846083 Evaluation's auc: 0.827229 [155] Train's auc: 0.846165 Evaluation's auc: 0.827246 [156] Train's auc: 0.846424 Evaluation's auc: 0.82743 [157] Train's auc: 0.8465 Evaluation's auc: 0.827464 [158] Train's auc: 0.846678 Evaluation's auc: 0.827695 [159] Train's auc: 0.846806 Evaluation's auc: 0.827744 [160] Train's auc: 0.847041 Evaluation's auc: 0.827913 [161] Train's auc: 0.847134 Evaluation's auc: 0.827959 [162] Train's auc: 0.847269 Evaluation's auc: 0.828101 [163] Train's auc: 0.847342 Evaluation's auc: 0.828153 [164] Train's auc: 0.847453 Evaluation's auc: 0.828225 [165] Train's auc: 0.847552 Evaluation's auc: 0.828273 [166] Train's auc: 0.847667 Evaluation's auc: 0.828414 [167] Train's auc: 0.847852 Evaluation's auc: 0.828574 [168] Train's auc: 0.847923 Evaluation's auc: 0.828592 [169] Train's auc: 0.847999 Evaluation's auc: 0.828603 [170] Train's auc: 0.848097 Evaluation's auc: 0.828666 [171] Train's auc: 0.84827 Evaluation's auc: 0.828764 [172] Train's auc: 0.848453 Evaluation's auc: 0.828881 [173] Train's auc: 0.848551 Evaluation's auc: 0.829004 [174] Train's auc: 0.848623 Evaluation's auc: 0.828993 [175] Train's auc: 0.848701 Evaluation's auc: 0.829012 [176] Train's auc: 0.848781 Evaluation's auc: 0.829036 [177] Train's auc: 0.848843 Evaluation's auc: 0.829089 [178] Train's auc: 0.84893 Evaluation's auc: 0.829044 [179] Train's auc: 0.848994 Evaluation's auc: 0.829062 [180] Train's auc: 0.849083 Evaluation's auc: 0.829123 [181] Train's auc: 0.849267 Evaluation's auc: 0.829272 [182] Train's auc: 0.849606 Evaluation's auc: 0.829627 [183] Train's auc: 0.849662 Evaluation's auc: 0.829632 [184] Train's auc: 0.849721 Evaluation's auc: 0.829666 [185] Train's auc: 0.849782 Evaluation's auc: 0.829685 [186] Train's auc: 0.849894 Evaluation's auc: 0.829786 [187] Train's auc: 0.850007 Evaluation's auc: 0.829843 [188] Train's auc: 0.850051 Evaluation's auc: 0.829924 [189] Train's auc: 0.850112 Evaluation's auc: 0.829904 [190] Train's auc: 0.850215 Evaluation's auc: 0.830009 [191] Train's auc: 0.850352 Evaluation's auc: 0.830142 [192] Train's auc: 0.850499 Evaluation's auc: 0.830301 [193] Train's auc: 0.850578 Evaluation's auc: 0.830378 [194] Train's auc: 0.850639 Evaluation's auc: 0.830402 [195] Train's auc: 0.850685 Evaluation's auc: 0.830457 [196] Train's auc: 0.850764 Evaluation's auc: 0.830546 [197] Train's auc: 0.850861 Evaluation's auc: 0.83065 [198] Train's auc: 0.850907 Evaluation's auc: 0.830616 [199] Train's auc: 0.850988 Evaluation's auc: 0.83067 [200] Train's auc: 0.851054 Evaluation's auc: 0.830681 [201] Train's auc: 0.851154 Evaluation's auc: 0.830771 [202] Train's auc: 0.851222 Evaluation's auc: 0.830837 [203] Train's auc: 0.851335 Evaluation's auc: 0.830908 [204] Train's auc: 0.851397 Evaluation's auc: 0.830942 [205] Train's auc: 0.8515 Evaluation's auc: 0.83094 [206] Train's auc: 0.851551 Evaluation's auc: 0.830978 [207] Train's auc: 0.851639 Evaluation's auc: 0.831026 [208] Train's auc: 0.851692 Evaluation's auc: 0.831043 [209] Train's auc: 0.851749 Evaluation's auc: 0.831067 [210] Train's auc: 0.851801 Evaluation's auc: 0.831083 [211] Train's auc: 0.851915 Evaluation's auc: 0.831173 [212] Train's auc: 0.852023 Evaluation's auc: 0.831178 [213] Train's auc: 0.852151 Evaluation's auc: 0.831231 [214] Train's auc: 0.852197 Evaluation's auc: 0.831234 [215] Train's auc: 0.852222 Evaluation's auc: 0.831248 [216] Train's auc: 0.852357 Evaluation's auc: 0.831317 [217] Train's auc: 0.852426 Evaluation's auc: 0.831324 [218] Train's auc: 0.852517 Evaluation's auc: 0.83135 [219] Train's auc: 0.852598 Evaluation's auc: 0.831322 [220] Train's auc: 0.852644 Evaluation's auc: 0.831347 [221] Train's auc: 0.852758 Evaluation's auc: 0.831416 [222] Train's auc: 0.852802 Evaluation's auc: 0.831431 [223] Train's auc: 0.852854 Evaluation's auc: 0.831415 [224] Train's auc: 0.853 Evaluation's auc: 0.831527 [225] Train's auc: 0.853062 Evaluation's auc: 0.831616 [226] Train's auc: 0.853472 Evaluation's auc: 0.831891 [227] Train's auc: 0.853516 Evaluation's auc: 0.831873 [228] Train's auc: 0.853606 Evaluation's auc: 0.831857 [229] Train's auc: 0.853707 Evaluation's auc: 0.831907 [230] Train's auc: 0.85376 Evaluation's auc: 0.831888 [231] Train's auc: 0.85382 Evaluation's auc: 0.831883 [232] Train's auc: 0.853876 Evaluation's auc: 0.831913 [233] Train's auc: 0.853943 Evaluation's auc: 0.832018 [234] Train's auc: 0.854088 Evaluation's auc: 0.832205 [235] Train's auc: 0.854208 Evaluation's auc: 0.832295 [236] Train's auc: 0.854264 Evaluation's auc: 0.83229 [237] Train's auc: 0.85458 Evaluation's auc: 0.832474 [238] Train's auc: 0.854712 Evaluation's auc: 0.832476 [239] Train's auc: 0.854762 Evaluation's auc: 0.83248 [240] Train's auc: 0.854857 Evaluation's auc: 0.832527 [241] Train's auc: 0.854947 Evaluation's auc: 0.832612 [242] Train's auc: 0.855024 Evaluation's auc: 0.83265 [243] Train's auc: 0.855142 Evaluation's auc: 0.832769 [244] Train's auc: 0.855227 Evaluation's auc: 0.832807 [245] Train's auc: 0.855345 Evaluation's auc: 0.832793 [246] Train's auc: 0.855409 Evaluation's auc: 0.832762 [247] Train's auc: 0.855438 Evaluation's auc: 0.832741 [248] Train's auc: 0.855469 Evaluation's auc: 0.832725 [249] Train's auc: 0.855579 Evaluation's auc: 0.832885 [250] Train's auc: 0.855653 Evaluation's auc: 0.832972 [251] Train's auc: 0.855861 Evaluation's auc: 0.833177 [252] Train's auc: 0.855906 Evaluation's auc: 0.833206 [253] Train's auc: 0.856003 Evaluation's auc: 0.833255 [254] Train's auc: 0.856049 Evaluation's auc: 0.833269 [255] Train's auc: 0.856164 Evaluation's auc: 0.833381 [256] Train's auc: 0.856251 Evaluation's auc: 0.833416 [257] Train's auc: 0.856328 Evaluation's auc: 0.8335 [258] Train's auc: 0.856428 Evaluation's auc: 0.83363 [259] Train's auc: 0.856489 Evaluation's auc: 0.833655 [260] Train's auc: 0.856548 Evaluation's auc: 0.833692 [261] Train's auc: 0.856633 Evaluation's auc: 0.833748 [262] Train's auc: 0.856672 Evaluation's auc: 0.833746 [263] Train's auc: 0.856783 Evaluation's auc: 0.833799 [264] Train's auc: 0.856855 Evaluation's auc: 0.833868 [265] Train's auc: 0.856914 Evaluation's auc: 0.833862 [266] Train's auc: 0.857004 Evaluation's auc: 0.833923 [267] Train's auc: 0.857051 Evaluation's auc: 0.833934 [268] Train's auc: 0.85713 Evaluation's auc: 0.833993 [269] Train's auc: 0.857182 Evaluation's auc: 0.833982 [270] Train's auc: 0.857235 Evaluation's auc: 0.834035 [271] Train's auc: 0.85731 Evaluation's auc: 0.834078 [272] Train's auc: 0.857389 Evaluation's auc: 0.834108 [273] Train's auc: 0.857462 Evaluation's auc: 0.834147 [274] Train's auc: 0.857527 Evaluation's auc: 0.834167 [275] Train's auc: 0.857586 Evaluation's auc: 0.834139 [276] Train's auc: 0.857618 Evaluation's auc: 0.834148 [277] Train's auc: 0.857679 Evaluation's auc: 0.834163 [278] Train's auc: 0.857729 Evaluation's auc: 0.834175 [279] Train's auc: 0.857769 Evaluation's auc: 0.834139 [280] Train's auc: 0.857832 Evaluation's auc: 0.834192 [281] Train's auc: 0.857974 Evaluation's auc: 0.834372 [282] Train's auc: 0.85802 Evaluation's auc: 0.834437 [283] Train's auc: 0.858146 Evaluation's auc: 0.834523 [284] Train's auc: 0.85823 Evaluation's auc: 0.834543 [285] Train's auc: 0.858297 Evaluation's auc: 0.834533 [286] Train's auc: 0.858367 Evaluation's auc: 0.834574 [287] Train's auc: 0.858401 Evaluation's auc: 0.834589 [288] Train's auc: 0.85849 Evaluation's auc: 0.8346 [289] Train's auc: 0.858548 Evaluation's auc: 0.834593 [290] Train's auc: 0.858624 Evaluation's auc: 0.834658 [291] Train's auc: 0.85871 Evaluation's auc: 0.834722 [292] Train's auc: 0.858787 Evaluation's auc: 0.834758 [293] Train's auc: 0.858866 Evaluation's auc: 0.834807 [294] Train's auc: 0.858914 Evaluation's auc: 0.834793 [295] Train's auc: 0.858957 Evaluation's auc: 0.834748 [296] Train's auc: 0.859066 Evaluation's auc: 0.834849 [297] Train's auc: 0.859177 Evaluation's auc: 0.834885 [298] Train's auc: 0.85926 Evaluation's auc: 0.834955 [299] Train's auc: 0.859311 Evaluation's auc: 0.834977 [300] Train's auc: 0.859363 Evaluation's auc: 0.835021 [301] Train's auc: 0.859438 Evaluation's auc: 0.835025 [302] Train's auc: 0.859491 Evaluation's auc: 0.83501 [303] Train's auc: 0.859553 Evaluation's auc: 0.835087 [304] Train's auc: 0.859575 Evaluation's auc: 0.835085 [305] Train's auc: 0.859617 Evaluation's auc: 0.83508 [306] Train's auc: 0.859678 Evaluation's auc: 0.835104 [307] Train's auc: 0.859721 Evaluation's auc: 0.83512 [308] Train's auc: 0.859751 Evaluation's auc: 0.835118 [309] Train's auc: 0.859833 Evaluation's auc: 0.835158 [310] Train's auc: 0.859882 Evaluation's auc: 0.835231 [311] Train's auc: 0.859913 Evaluation's auc: 0.835268 [312] Train's auc: 0.85998 Evaluation's auc: 0.835274 [313] Train's auc: 0.860046 Evaluation's auc: 0.835299 [314] Train's auc: 0.860176 Evaluation's auc: 0.835401 [315] Train's auc: 0.860263 Evaluation's auc: 0.835469 [316] Train's auc: 0.860331 Evaluation's auc: 0.83557 [317] Train's auc: 0.860411 Evaluation's auc: 0.835615 [318] Train's auc: 0.860475 Evaluation's auc: 0.835652 [319] Train's auc: 0.860541 Evaluation's auc: 0.8357 [320] Train's auc: 0.860609 Evaluation's auc: 0.835712 [321] Train's auc: 0.860639 Evaluation's auc: 0.835756 [322] Train's auc: 0.860705 Evaluation's auc: 0.835821 [323] Train's auc: 0.860738 Evaluation's auc: 0.835811 [324] Train's auc: 0.860783 Evaluation's auc: 0.835821 [325] Train's auc: 0.860865 Evaluation's auc: 0.835858 [326] Train's auc: 0.86092 Evaluation's auc: 0.835876 [327] Train's auc: 0.860982 Evaluation's auc: 0.835885 [328] Train's auc: 0.861026 Evaluation's auc: 0.835848 [329] Train's auc: 0.861087 Evaluation's auc: 0.835832 [330] Train's auc: 0.861123 Evaluation's auc: 0.835862 [331] Train's auc: 0.861181 Evaluation's auc: 0.835889 [332] Train's auc: 0.861314 Evaluation's auc: 0.836045 [333] Train's auc: 0.861361 Evaluation's auc: 0.836054 [334] Train's auc: 0.861468 Evaluation's auc: 0.836142 [335] Train's auc: 0.861511 Evaluation's auc: 0.836134 [336] Train's auc: 0.861617 Evaluation's auc: 0.836181 [337] Train's auc: 0.86168 Evaluation's auc: 0.83619 [338] Train's auc: 0.861757 Evaluation's auc: 0.836247 [339] Train's auc: 0.861815 Evaluation's auc: 0.836277 [340] Train's auc: 0.861865 Evaluation's auc: 0.836348 [341] Train's auc: 0.861928 Evaluation's auc: 0.836321 [342] Train's auc: 0.862031 Evaluation's auc: 0.836468 [343] Train's auc: 0.86214 Evaluation's auc: 0.83656 [344] Train's auc: 0.862194 Evaluation's auc: 0.836562 [345] Train's auc: 0.862245 Evaluation's auc: 0.83655 [346] Train's auc: 0.862279 Evaluation's auc: 0.836562 [347] Train's auc: 0.862341 Evaluation's auc: 0.836602 [348] Train's auc: 0.862432 Evaluation's auc: 0.836614 [349] Train's auc: 0.862464 Evaluation's auc: 0.836629 [350] Train's auc: 0.862502 Evaluation's auc: 0.836602 [351] Train's auc: 0.862565 Evaluation's auc: 0.836625 [352] Train's auc: 0.862595 Evaluation's auc: 0.836588 [353] Train's auc: 0.86264 Evaluation's auc: 0.836589 [354] Train's auc: 0.862715 Evaluation's auc: 0.836612 [355] Train's auc: 0.86275 Evaluation's auc: 0.836651 [356] Train's auc: 0.862806 Evaluation's auc: 0.836678 [357] Train's auc: 0.862861 Evaluation's auc: 0.836681 [358] Train's auc: 0.862909 Evaluation's auc: 0.836699 [359] Train's auc: 0.862948 Evaluation's auc: 0.836687 [360] Train's auc: 0.862995 Evaluation's auc: 0.836645 [361] Train's auc: 0.863047 Evaluation's auc: 0.836657 [362] Train's auc: 0.86308 Evaluation's auc: 0.836676 [363] Train's auc: 0.863148 Evaluation's auc: 0.836726 [364] Train's auc: 0.863191 Evaluation's auc: 0.836752 [365] Train's auc: 0.863294 Evaluation's auc: 0.836892 [366] Train's auc: 0.863332 Evaluation's auc: 0.836914 [367] Train's auc: 0.863402 Evaluation's auc: 0.836941 [368] Train's auc: 0.863463 Evaluation's auc: 0.836975 [369] Train's auc: 0.863536 Evaluation's auc: 0.837029 [370] Train's auc: 0.863587 Evaluation's auc: 0.837016 [371] Train's auc: 0.863628 Evaluation's auc: 0.836997 [372] Train's auc: 0.863711 Evaluation's auc: 0.837043 [373] Train's auc: 0.863756 Evaluation's auc: 0.837066 [374] Train's auc: 0.86381 Evaluation's auc: 0.837103 [375] Train's auc: 0.863857 Evaluation's auc: 0.837098 [376] Train's auc: 0.863908 Evaluation's auc: 0.837101 [377] Train's auc: 0.863976 Evaluation's auc: 0.83709 [378] Train's auc: 0.864013 Evaluation's auc: 0.837099 [379] Train's auc: 0.864066 Evaluation's auc: 0.837082 [380] Train's auc: 0.864101 Evaluation's auc: 0.837043 [381] Train's auc: 0.864171 Evaluation's auc: 0.837044 [382] Train's auc: 0.864244 Evaluation's auc: 0.837104 [383] Train's auc: 0.86428 Evaluation's auc: 0.837045 [384] Train's auc: 0.864325 Evaluation's auc: 0.837111 [385] Train's auc: 0.864376 Evaluation's auc: 0.837141 [386] Train's auc: 0.864444 Evaluation's auc: 0.837169 [387] Train's auc: 0.864498 Evaluation's auc: 0.837162 [388] Train's auc: 0.864535 Evaluation's auc: 0.837208 [389] Train's auc: 0.864577 Evaluation's auc: 0.837253 [390] Train's auc: 0.864633 Evaluation's auc: 0.837277 [391] Train's auc: 0.864706 Evaluation's auc: 0.837277 [392] Train's auc: 0.864759 Evaluation's auc: 0.837269 [393] Train's auc: 0.864804 Evaluation's auc: 0.837275 [394] Train's auc: 0.864847 Evaluation's auc: 0.837288 [395] Train's auc: 0.864927 Evaluation's auc: 0.837292 [396] Train's auc: 0.864992 Evaluation's auc: 0.837265 [397] Train's auc: 0.865023 Evaluation's auc: 0.837285 [398] Train's auc: 0.865076 Evaluation's auc: 0.837318 [399] Train's auc: 0.86513 Evaluation's auc: 0.837329 [400] Train's auc: 0.865163 Evaluation's auc: 0.837315 [401] Train's auc: 0.865235 Evaluation's auc: 0.837425 [402] Train's auc: 0.865278 Evaluation's auc: 0.837429 [403] Train's auc: 0.865347 Evaluation's auc: 0.837463 [404] Train's auc: 0.865395 Evaluation's auc: 0.837476 [405] Train's auc: 0.865445 Evaluation's auc: 0.837513 [406] Train's auc: 0.865509 Evaluation's auc: 0.837608 [407] Train's auc: 0.865583 Evaluation's auc: 0.837628 [408] Train's auc: 0.865657 Evaluation's auc: 0.837651 [409] Train's auc: 0.865691 Evaluation's auc: 0.837662 [410] Train's auc: 0.865719 Evaluation's auc: 0.837663 [411] Train's auc: 0.865762 Evaluation's auc: 0.837661 [412] Train's auc: 0.865787 Evaluation's auc: 0.837649 [413] Train's auc: 0.865807 Evaluation's auc: 0.837641 [414] Train's auc: 0.865838 Evaluation's auc: 0.837637 [415] Train's auc: 0.86589 Evaluation's auc: 0.837615 [416] Train's auc: 0.865957 Evaluation's auc: 0.837637 [417] Train's auc: 0.866009 Evaluation's auc: 0.837625 [418] Train's auc: 0.866055 Evaluation's auc: 0.837585 [419] Train's auc: 0.866098 Evaluation's auc: 0.83758 [420] Train's auc: 0.866142 Evaluation's auc: 0.837605 [421] Train's auc: 0.866197 Evaluation's auc: 0.837613 [422] Train's auc: 0.866269 Evaluation's auc: 0.837672 [423] Train's auc: 0.866307 Evaluation's auc: 0.837675 [424] Train's auc: 0.866347 Evaluation's auc: 0.837661 [425] Train's auc: 0.866389 Evaluation's auc: 0.837677 [426] Train's auc: 0.866457 Evaluation's auc: 0.837724 [427] Train's auc: 0.866512 Evaluation's auc: 0.837724 [428] Train's auc: 0.866564 Evaluation's auc: 0.837758 [429] Train's auc: 0.866643 Evaluation's auc: 0.837798 [430] Train's auc: 0.866706 Evaluation's auc: 0.837788 [431] Train's auc: 0.86676 Evaluation's auc: 0.837793 [432] Train's auc: 0.866833 Evaluation's auc: 0.837856 [433] Train's auc: 0.866912 Evaluation's auc: 0.837887 [434] Train's auc: 0.866977 Evaluation's auc: 0.837885 [435] Train's auc: 0.867031 Evaluation's auc: 0.837877 [436] Train's auc: 0.867067 Evaluation's auc: 0.837868 [437] Train's auc: 0.867124 Evaluation's auc: 0.837867 [438] Train's auc: 0.867175 Evaluation's auc: 0.837859 [439] Train's auc: 0.867208 Evaluation's auc: 0.837878 [440] Train's auc: 0.867237 Evaluation's auc: 0.8379 [441] Train's auc: 0.867289 Evaluation's auc: 0.837917 [442] Train's auc: 0.867318 Evaluation's auc: 0.837927 [443] Train's auc: 0.867371 Evaluation's auc: 0.837949 [444] Train's auc: 0.867403 Evaluation's auc: 0.837962 [445] Train's auc: 0.867468 Evaluation's auc: 0.837981 [446] Train's auc: 0.867526 Evaluation's auc: 0.838007 [447] Train's auc: 0.867579 Evaluation's auc: 0.83802 [448] Train's auc: 0.867618 Evaluation's auc: 0.838004 [449] Train's auc: 0.867709 Evaluation's auc: 0.838125 [450] Train's auc: 0.867733 Evaluation's auc: 0.838112 [451] Train's auc: 0.867782 Evaluation's auc: 0.838121 [452] Train's auc: 0.867808 Evaluation's auc: 0.838119 [453] Train's auc: 0.867855 Evaluation's auc: 0.83813 [454] Train's auc: 0.867902 Evaluation's auc: 0.838111 [455] Train's auc: 0.867955 Evaluation's auc: 0.838137 [456] Train's auc: 0.868002 Evaluation's auc: 0.838157 [457] Train's auc: 0.868092 Evaluation's auc: 0.838249 [458] Train's auc: 0.868132 Evaluation's auc: 0.838296 [459] Train's auc: 0.868212 Evaluation's auc: 0.838395 [460] Train's auc: 0.868254 Evaluation's auc: 0.838364 [461] Train's auc: 0.868282 Evaluation's auc: 0.838337 [462] Train's auc: 0.868312 Evaluation's auc: 0.838348 [463] Train's auc: 0.86839 Evaluation's auc: 0.838409 [464] Train's auc: 0.868445 Evaluation's auc: 0.838417 [465] Train's auc: 0.86848 Evaluation's auc: 0.838431 [466] Train's auc: 0.868522 Evaluation's auc: 0.838405 [467] Train's auc: 0.868552 Evaluation's auc: 0.838433 [468] Train's auc: 0.868588 Evaluation's auc: 0.838447 [469] Train's auc: 0.868644 Evaluation's auc: 0.838476 [470] Train's auc: 0.868682 Evaluation's auc: 0.838463 [471] Train's auc: 0.868751 Evaluation's auc: 0.838515 [472] Train's auc: 0.868825 Evaluation's auc: 0.838557 [473] Train's auc: 0.868857 Evaluation's auc: 0.838542 [474] Train's auc: 0.868913 Evaluation's auc: 0.838562 [475] Train's auc: 0.868971 Evaluation's auc: 0.838572 [476] Train's auc: 0.869025 Evaluation's auc: 0.838609 [477] Train's auc: 0.869059 Evaluation's auc: 0.838611 [478] Train's auc: 0.869109 Evaluation's auc: 0.838612 [479] Train's auc: 0.869134 Evaluation's auc: 0.838582 [480] Train's auc: 0.869165 Evaluation's auc: 0.8386 [481] Train's auc: 0.869221 Evaluation's auc: 0.838633 [482] Train's auc: 0.869258 Evaluation's auc: 0.838597 [483] Train's auc: 0.869294 Evaluation's auc: 0.838588 [484] Train's auc: 0.869348 Evaluation's auc: 0.838589 [485] Train's auc: 0.869401 Evaluation's auc: 0.83861 [486] Train's auc: 0.869423 Evaluation's auc: 0.838599 [487] Train's auc: 0.869469 Evaluation's auc: 0.838615 [488] Train's auc: 0.8695 Evaluation's auc: 0.838636 [489] Train's auc: 0.86953 Evaluation's auc: 0.838615 [490] Train's auc: 0.869561 Evaluation's auc: 0.838606 [491] Train's auc: 0.86968 Evaluation's auc: 0.838676 [492] Train's auc: 0.869707 Evaluation's auc: 0.838665 [493] Train's auc: 0.869781 Evaluation's auc: 0.838672 [494] Train's auc: 0.869868 Evaluation's auc: 0.83874 [495] Train's auc: 0.869892 Evaluation's auc: 0.838729 [496] Train's auc: 0.869933 Evaluation's auc: 0.838727 [497] Train's auc: 0.86997 Evaluation's auc: 0.838736 [498] Train's auc: 0.870018 Evaluation's auc: 0.838744 [499] Train's auc: 0.870077 Evaluation's auc: 0.838746 [500] Train's auc: 0.870147 Evaluation's auc: 0.838776 [501] Train's auc: 0.870192 Evaluation's auc: 0.838761 [502] Train's auc: 0.87021 Evaluation's auc: 0.838759 [503] Train's auc: 0.870233 Evaluation's auc: 0.838763 [504] Train's auc: 0.870295 Evaluation's auc: 0.838758 [505] Train's auc: 0.87031 Evaluation's auc: 0.83874 [506] Train's auc: 0.870351 Evaluation's auc: 0.838745 [507] Train's auc: 0.870397 Evaluation's auc: 0.838804 [508] Train's auc: 0.870428 Evaluation's auc: 0.838808 [509] Train's auc: 0.870466 Evaluation's auc: 0.838813 [510] Train's auc: 0.870498 Evaluation's auc: 0.838784 [511] Train's auc: 0.870519 Evaluation's auc: 0.83877 [512] Train's auc: 0.870546 Evaluation's auc: 0.838765 [513] Train's auc: 0.87059 Evaluation's auc: 0.838765 [514] Train's auc: 0.870644 Evaluation's auc: 0.838791 [515] Train's auc: 0.870665 Evaluation's auc: 0.838766 [516] Train's auc: 0.870699 Evaluation's auc: 0.838738 [517] Train's auc: 0.87074 Evaluation's auc: 0.838735 [518] Train's auc: 0.870777 Evaluation's auc: 0.838777 [519] Train's auc: 0.870828 Evaluation's auc: 0.838827 [520] Train's auc: 0.870942 Evaluation's auc: 0.838948 [521] Train's auc: 0.870962 Evaluation's auc: 0.838946 [522] Train's auc: 0.87103 Evaluation's auc: 0.838993 [523] Train's auc: 0.871083 Evaluation's auc: 0.838979 [524] Train's auc: 0.871117 Evaluation's auc: 0.838982 [525] Train's auc: 0.871174 Evaluation's auc: 0.839026 [526] Train's auc: 0.87121 Evaluation's auc: 0.839042 [527] Train's auc: 0.871271 Evaluation's auc: 0.839044 [528] Train's auc: 0.871315 Evaluation's auc: 0.839064 [529] Train's auc: 0.871345 Evaluation's auc: 0.839064 [530] Train's auc: 0.871381 Evaluation's auc: 0.839066 [531] Train's auc: 0.871426 Evaluation's auc: 0.839094 [532] Train's auc: 0.871457 Evaluation's auc: 0.8391 [533] Train's auc: 0.871503 Evaluation's auc: 0.839101 [534] Train's auc: 0.871553 Evaluation's auc: 0.839126 [535] Train's auc: 0.871596 Evaluation's auc: 0.839082 [536] Train's auc: 0.871653 Evaluation's auc: 0.839129 [537] Train's auc: 0.871699 Evaluation's auc: 0.839162 [538] Train's auc: 0.871799 Evaluation's auc: 0.83925 [539] Train's auc: 0.871839 Evaluation's auc: 0.839226 [540] Train's auc: 0.871916 Evaluation's auc: 0.839307 [541] Train's auc: 0.87197 Evaluation's auc: 0.839312 [542] Train's auc: 0.872009 Evaluation's auc: 0.839326 [543] Train's auc: 0.872049 Evaluation's auc: 0.839368 [544] Train's auc: 0.872084 Evaluation's auc: 0.839388 [545] Train's auc: 0.872118 Evaluation's auc: 0.839379 [546] Train's auc: 0.872153 Evaluation's auc: 0.839386 [547] Train's auc: 0.872251 Evaluation's auc: 0.839517 [548] Train's auc: 0.872323 Evaluation's auc: 0.839589 [549] Train's auc: 0.872374 Evaluation's auc: 0.839577 [550] Train's auc: 0.872398 Evaluation's auc: 0.83958 [551] Train's auc: 0.872465 Evaluation's auc: 0.839643 [552] Train's auc: 0.872519 Evaluation's auc: 0.839671 [553] Train's auc: 0.872557 Evaluation's auc: 0.839663 [554] Train's auc: 0.872612 Evaluation's auc: 0.839647 [555] Train's auc: 0.872633 Evaluation's auc: 0.839651 [556] Train's auc: 0.872684 Evaluation's auc: 0.839651 [557] Train's auc: 0.872723 Evaluation's auc: 0.839635 [558] Train's auc: 0.872764 Evaluation's auc: 0.83965 [559] Train's auc: 0.872818 Evaluation's auc: 0.8397 [560] Train's auc: 0.872893 Evaluation's auc: 0.839814 [561] Train's auc: 0.872933 Evaluation's auc: 0.83984 [562] Train's auc: 0.873 Evaluation's auc: 0.839859 [563] Train's auc: 0.873036 Evaluation's auc: 0.839894 [564] Train's auc: 0.873056 Evaluation's auc: 0.839884 [565] Train's auc: 0.873095 Evaluation's auc: 0.839881 [566] Train's auc: 0.87312 Evaluation's auc: 0.839875 [567] Train's auc: 0.873144 Evaluation's auc: 0.839906 [568] Train's auc: 0.873169 Evaluation's auc: 0.839913 [569] Train's auc: 0.873229 Evaluation's auc: 0.840007 [570] Train's auc: 0.873303 Evaluation's auc: 0.840098 [571] Train's auc: 0.873358 Evaluation's auc: 0.840123 [572] Train's auc: 0.873401 Evaluation's auc: 0.840153 [573] Train's auc: 0.873432 Evaluation's auc: 0.840182 [574] Train's auc: 0.873494 Evaluation's auc: 0.840202 [575] Train's auc: 0.873535 Evaluation's auc: 0.840202 [576] Train's auc: 0.873581 Evaluation's auc: 0.840241 [577] Train's auc: 0.873625 Evaluation's auc: 0.840261 [578] Train's auc: 0.873686 Evaluation's auc: 0.840284 [579] Train's auc: 0.873715 Evaluation's auc: 0.840258 [580] Train's auc: 0.873747 Evaluation's auc: 0.840257 [581] Train's auc: 0.873798 Evaluation's auc: 0.840262 [582] Train's auc: 0.873837 Evaluation's auc: 0.840261 [583] Train's auc: 0.873878 Evaluation's auc: 0.840281 [584] Train's auc: 0.873939 Evaluation's auc: 0.840304 [585] Train's auc: 0.874006 Evaluation's auc: 0.840329 [586] Train's auc: 0.874053 Evaluation's auc: 0.840363 [587] Train's auc: 0.874101 Evaluation's auc: 0.840391 [588] Train's auc: 0.874145 Evaluation's auc: 0.840403 [589] Train's auc: 0.874201 Evaluation's auc: 0.840441 [590] Train's auc: 0.874249 Evaluation's auc: 0.840483 [591] Train's auc: 0.874291 Evaluation's auc: 0.840526 [592] Train's auc: 0.874308 Evaluation's auc: 0.840531 [593] Train's auc: 0.874334 Evaluation's auc: 0.840534 [594] Train's auc: 0.874377 Evaluation's auc: 0.840556 [595] Train's auc: 0.874412 Evaluation's auc: 0.840547 [596] Train's auc: 0.874429 Evaluation's auc: 0.840534 [597] Train's auc: 0.874462 Evaluation's auc: 0.840572 [598] Train's auc: 0.874523 Evaluation's auc: 0.840597 [599] Train's auc: 0.874557 Evaluation's auc: 0.840599 [600] Train's auc: 0.874572 Evaluation's auc: 0.840625 [601] Train's auc: 0.87461 Evaluation's auc: 0.840682 [602] Train's auc: 0.874627 Evaluation's auc: 0.840693 [603] Train's auc: 0.87468 Evaluation's auc: 0.840705 [604] Train's auc: 0.874717 Evaluation's auc: 0.840693 [605] Train's auc: 0.874739 Evaluation's auc: 0.840683 [606] Train's auc: 0.874771 Evaluation's auc: 0.840681 [607] Train's auc: 0.87483 Evaluation's auc: 0.840702 [608] Train's auc: 0.874874 Evaluation's auc: 0.840712 [609] Train's auc: 0.874888 Evaluation's auc: 0.840688 [610] Train's auc: 0.87491 Evaluation's auc: 0.840721 [611] Train's auc: 0.874951 Evaluation's auc: 0.840729 [612] Train's auc: 0.874979 Evaluation's auc: 0.840722 [613] Train's auc: 0.874995 Evaluation's auc: 0.840712 [614] Train's auc: 0.875018 Evaluation's auc: 0.840695 [615] Train's auc: 0.875039 Evaluation's auc: 0.840659 [616] Train's auc: 0.875069 Evaluation's auc: 0.840694 [617] Train's auc: 0.875106 Evaluation's auc: 0.84071 [618] Train's auc: 0.875142 Evaluation's auc: 0.840668 [619] Train's auc: 0.875178 Evaluation's auc: 0.840651 [620] Train's auc: 0.875211 Evaluation's auc: 0.840649 [621] Train's auc: 0.875261 Evaluation's auc: 0.840674 [622] Train's auc: 0.875281 Evaluation's auc: 0.840688 [623] Train's auc: 0.875325 Evaluation's auc: 0.840679 [624] Train's auc: 0.875361 Evaluation's auc: 0.84069 [625] Train's auc: 0.875397 Evaluation's auc: 0.840673 [626] Train's auc: 0.875435 Evaluation's auc: 0.840662 [627] Train's auc: 0.875473 Evaluation's auc: 0.84065 [628] Train's auc: 0.875521 Evaluation's auc: 0.840631 [629] Train's auc: 0.875571 Evaluation's auc: 0.840691 [630] Train's auc: 0.875616 Evaluation's auc: 0.840705 [631] Train's auc: 0.875644 Evaluation's auc: 0.8407 Early stopping, best iteration is: [611] Train's auc: 0.874951 Evaluation's auc: 0.840729
y_pred = gbm_rh.predict(x_val)
y_pred = np.where(y_pred > 0.5, 1, 0) # convert into binary values
# Accuracy
from sklearn.metrics import accuracy_score
accuracy = accuracy_score(y_pred, y_val)
accuracy
0.824765625
# Confusion matrix
from sklearn.metrics import confusion_matrix
cm = confusion_matrix(y_val, y_pred)
cm
array([[9410, 607],
[1636, 1147]])
# We can concatenate x_train and x_val
dfs = [x_train, x_val]
dfsy = [y_train, y_val]
x_train_rf = pd.concat(dfs)
y_train_rf = pd.concat(dfsy)
lightgbm_hp_train = lgb.Dataset(x_train_rf, y_train_rf)
lightgbm_hp_train = lgb.Dataset(x_train, y_train)
lightgbm_hp_val = lgb.Dataset(x_val, y_val)
# Sets the space to search over and the prior probabilities over the search space
lgbm_space = {
# hp.choice.choice will select 1 value from the given list , 'dart', 'goss', 'rf'
'boosting_type': hp.hp.choice('boosting_type', ['gbdt']),
'num_leaves':hp.hp.choice('num_leaves', np.arange(10, 300,1, dtype=int)),
'subsample':hp.hp.quniform('subsample',0.5,1.0,0.05),
'colsample_bytree':hp.hp.quniform('colsample_bytree',0.5,1.0,0.05),
'min_child_weight':hp.hp.quniform('min_child_weight', 100, 1000,100),
'reg_alpha': hp.hp.uniform('reg_alpha', 0.0, 1000.0),
'reg_lambda': hp.hp.uniform('reg_lambda', 0.0, 1000.0),
'learning_rate': hp.hp.loguniform('learning_rate', -4, 0),
'feature_fraction': hp.hp.loguniform('feature_fraction', -4, 0),
'bagging_fraction': hp.hp.loguniform('bagging_fraction', -4, 0),
'bagging_frequency':hp.hp.choice('bagging_frequency', np.arange(5, 100,1, dtype=int)),
'drop_rate': hp.hp.loguniform('drop_rate', -4, 0),
'scale_pos_weight': hp.hp.uniform('scale_pos_weight', 6.0, 10.0),
'metric' : 'auc',
'nthread': 6,
'max_bin': 512
}
# Here we define an objective (loss) function I take
def objective_m(params, n_folds=5):
model = lgb.cv(params = params,
train_set = lightgbm_hp_train,
num_boost_round = 10000,
early_stopping_rounds = 10,
nfold = n_folds)
# Returns the best average loss on validation set
loss = 1 - (max(model['auc-mean']))
return loss
bayes_trials = Trials()
MAX_EVALS = 10 # this controls the runtime
lgbm_best_m = fmin(fn = objective_m, space = lgbm_space, algo = hp.tpe.suggest,
max_evals = MAX_EVALS, trials = bayes_trials)
100%|██████████| 10/10 [00:13<00:00, 1.30s/trial, best loss: 0.17421290189754757]
# LightGBM best parameters
lgbm_best_m
{'bagging_fraction': 0.21835717243856412,
'bagging_frequency': 25,
'boosting_type': 0,
'colsample_bytree': 0.9,
'drop_rate': 0.09585306765988078,
'feature_fraction': 0.39962859971210074,
'learning_rate': 0.29662173472784276,
'min_child_weight': 800.0,
'num_leaves': 114,
'reg_alpha': 108.33230702491204,
'reg_lambda': 756.4823876094997,
'scale_pos_weight': 8.768176035187624,
'subsample': 0.8}
# lgb parameters
lgb_params = {
'objective': 'binary',
'metric': 'auc',
'bagging_fraction': 0.13,
'bagging_frequency': 35,
'boosting_type': 'gbdt',
'colsample_bytree': 0.7,
'drop_rate': 0.49,
'feature_fraction': 0.77,
'learning_rate': 0.04,
'min_child_weight': 700.0,
'num_leaves': 201,
'reg_alpha': 73,
'reg_lambda': 958,
'scale_pos_weight': 6,
'subsample': 0.65,
'early_stopping_round' : 20,
}
lgb_proc_train_rh = lgb.Dataset(x_train, y_train)
lgb_proc_val_rh = lgb.Dataset(x_val, y_val)
gbm_rh = lgb.train(params = lgb_params, train_set = lgb_proc_train_rh,
num_boost_round = 5000, valid_sets = [lgb_proc_val_rh, lgb_proc_train_rh],
valid_names = ['Evaluation', 'Train'])
/Users/piumallick/anaconda3/lib/python3.7/site-packages/lightgbm/engine.py:153: UserWarning: Found `early_stopping_round` in params. Will use it instead of argument
warnings.warn("Found `{}` in params. Will use it instead of argument".format(alias))
[1] Train's auc: 0.682345 Evaluation's auc: 0.680424 Training until validation scores don't improve for 20 rounds [2] Train's auc: 0.684777 Evaluation's auc: 0.682685 [3] Train's auc: 0.685064 Evaluation's auc: 0.682793 [4] Train's auc: 0.704032 Evaluation's auc: 0.703819 [5] Train's auc: 0.707238 Evaluation's auc: 0.70653 [6] Train's auc: 0.711649 Evaluation's auc: 0.710117 [7] Train's auc: 0.715827 Evaluation's auc: 0.712948 [8] Train's auc: 0.717009 Evaluation's auc: 0.71484 [9] Train's auc: 0.724052 Evaluation's auc: 0.720211 [10] Train's auc: 0.72623 Evaluation's auc: 0.72208 [11] Train's auc: 0.727497 Evaluation's auc: 0.722427 [12] Train's auc: 0.730778 Evaluation's auc: 0.725339 [13] Train's auc: 0.730931 Evaluation's auc: 0.725185 [14] Train's auc: 0.732774 Evaluation's auc: 0.726345 [15] Train's auc: 0.741156 Evaluation's auc: 0.735334 [16] Train's auc: 0.741679 Evaluation's auc: 0.735319 [17] Train's auc: 0.742327 Evaluation's auc: 0.736243 [18] Train's auc: 0.74373 Evaluation's auc: 0.738387 [19] Train's auc: 0.748951 Evaluation's auc: 0.743527 [20] Train's auc: 0.749702 Evaluation's auc: 0.744021 [21] Train's auc: 0.751328 Evaluation's auc: 0.745851 [22] Train's auc: 0.757033 Evaluation's auc: 0.750455 [23] Train's auc: 0.760419 Evaluation's auc: 0.753609 [24] Train's auc: 0.760751 Evaluation's auc: 0.754055 [25] Train's auc: 0.762568 Evaluation's auc: 0.75586 [26] Train's auc: 0.763873 Evaluation's auc: 0.757298 [27] Train's auc: 0.767274 Evaluation's auc: 0.760369 [28] Train's auc: 0.768987 Evaluation's auc: 0.761772 [29] Train's auc: 0.771408 Evaluation's auc: 0.763401 [30] Train's auc: 0.772444 Evaluation's auc: 0.764248 [31] Train's auc: 0.773445 Evaluation's auc: 0.765193 [32] Train's auc: 0.774937 Evaluation's auc: 0.766818 [33] Train's auc: 0.777455 Evaluation's auc: 0.769038 [34] Train's auc: 0.778008 Evaluation's auc: 0.769484 [35] Train's auc: 0.778991 Evaluation's auc: 0.770404 [36] Train's auc: 0.780355 Evaluation's auc: 0.772013 [37] Train's auc: 0.781287 Evaluation's auc: 0.77276 [38] Train's auc: 0.782719 Evaluation's auc: 0.774058 [39] Train's auc: 0.784121 Evaluation's auc: 0.774906 [40] Train's auc: 0.78494 Evaluation's auc: 0.775636 [41] Train's auc: 0.785764 Evaluation's auc: 0.776307 [42] Train's auc: 0.787059 Evaluation's auc: 0.777668 [43] Train's auc: 0.787726 Evaluation's auc: 0.778195 [44] Train's auc: 0.789141 Evaluation's auc: 0.779472 [45] Train's auc: 0.789892 Evaluation's auc: 0.779898 [46] Train's auc: 0.79021 Evaluation's auc: 0.780354 [47] Train's auc: 0.790988 Evaluation's auc: 0.780988 [48] Train's auc: 0.791677 Evaluation's auc: 0.78142 [49] Train's auc: 0.792878 Evaluation's auc: 0.782477 [50] Train's auc: 0.793524 Evaluation's auc: 0.78305 [51] Train's auc: 0.794128 Evaluation's auc: 0.783434 [52] Train's auc: 0.794424 Evaluation's auc: 0.783719 [53] Train's auc: 0.794744 Evaluation's auc: 0.783896 [54] Train's auc: 0.795739 Evaluation's auc: 0.784787 [55] Train's auc: 0.796692 Evaluation's auc: 0.785545 [56] Train's auc: 0.797188 Evaluation's auc: 0.785848 [57] Train's auc: 0.797248 Evaluation's auc: 0.785944 [58] Train's auc: 0.797748 Evaluation's auc: 0.786236 [59] Train's auc: 0.798077 Evaluation's auc: 0.786397 [60] Train's auc: 0.798148 Evaluation's auc: 0.786502 [61] Train's auc: 0.798595 Evaluation's auc: 0.78677 [62] Train's auc: 0.799034 Evaluation's auc: 0.786984 [63] Train's auc: 0.799647 Evaluation's auc: 0.787409 [64] Train's auc: 0.800784 Evaluation's auc: 0.788479 [65] Train's auc: 0.801088 Evaluation's auc: 0.788708 [66] Train's auc: 0.801127 Evaluation's auc: 0.788857 [67] Train's auc: 0.801829 Evaluation's auc: 0.789394 [68] Train's auc: 0.802416 Evaluation's auc: 0.789864 [69] Train's auc: 0.802759 Evaluation's auc: 0.790021 [70] Train's auc: 0.804013 Evaluation's auc: 0.791301 [71] Train's auc: 0.805146 Evaluation's auc: 0.792287 [72] Train's auc: 0.806343 Evaluation's auc: 0.793446 [73] Train's auc: 0.806478 Evaluation's auc: 0.793683 [74] Train's auc: 0.806675 Evaluation's auc: 0.793764 [75] Train's auc: 0.806842 Evaluation's auc: 0.794032 [76] Train's auc: 0.807868 Evaluation's auc: 0.795029 [77] Train's auc: 0.808034 Evaluation's auc: 0.795108 [78] Train's auc: 0.808514 Evaluation's auc: 0.795514 [79] Train's auc: 0.809349 Evaluation's auc: 0.796362 [80] Train's auc: 0.809684 Evaluation's auc: 0.796624 [81] Train's auc: 0.809967 Evaluation's auc: 0.796716 [82] Train's auc: 0.810985 Evaluation's auc: 0.797692 [83] Train's auc: 0.811846 Evaluation's auc: 0.798567 [84] Train's auc: 0.81277 Evaluation's auc: 0.799562 [85] Train's auc: 0.813609 Evaluation's auc: 0.800464 [86] Train's auc: 0.814045 Evaluation's auc: 0.800851 [87] Train's auc: 0.814261 Evaluation's auc: 0.800975 [88] Train's auc: 0.81485 Evaluation's auc: 0.801499 [89] Train's auc: 0.815029 Evaluation's auc: 0.801643 [90] Train's auc: 0.815158 Evaluation's auc: 0.801856 [91] Train's auc: 0.81584 Evaluation's auc: 0.802437 [92] Train's auc: 0.816041 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auc: 0.842532 Evaluation's auc: 0.824664 [312] Train's auc: 0.842577 Evaluation's auc: 0.824683 [313] Train's auc: 0.842617 Evaluation's auc: 0.824682 [314] Train's auc: 0.842665 Evaluation's auc: 0.824723 [315] Train's auc: 0.842696 Evaluation's auc: 0.824735 [316] Train's auc: 0.842783 Evaluation's auc: 0.824806 [317] Train's auc: 0.842845 Evaluation's auc: 0.824854 [318] Train's auc: 0.8429 Evaluation's auc: 0.824894 [319] Train's auc: 0.842979 Evaluation's auc: 0.824941 [320] Train's auc: 0.843008 Evaluation's auc: 0.82496 [321] Train's auc: 0.843053 Evaluation's auc: 0.824987 [322] Train's auc: 0.843093 Evaluation's auc: 0.825016 [323] Train's auc: 0.843142 Evaluation's auc: 0.825061 [324] Train's auc: 0.84322 Evaluation's auc: 0.825112 [325] Train's auc: 0.843269 Evaluation's auc: 0.825135 [326] Train's auc: 0.843315 Evaluation's auc: 0.825161 [327] Train's auc: 0.843371 Evaluation's auc: 0.825187 [328] Train's auc: 0.843438 Evaluation's auc: 0.825263 [329] Train's auc: 0.843473 Evaluation's auc: 0.825309 [330] Train's auc: 0.843516 Evaluation's auc: 0.825347 [331] Train's auc: 0.843556 Evaluation's auc: 0.825375 [332] Train's auc: 0.843618 Evaluation's auc: 0.825403 [333] Train's auc: 0.843695 Evaluation's auc: 0.825454 [334] Train's auc: 0.843737 Evaluation's auc: 0.825476 [335] Train's auc: 0.843776 Evaluation's auc: 0.825501 [336] Train's auc: 0.843819 Evaluation's auc: 0.825514 [337] Train's auc: 0.843861 Evaluation's auc: 0.825529 [338] Train's auc: 0.843888 Evaluation's auc: 0.825541 [339] Train's auc: 0.843924 Evaluation's auc: 0.825573 [340] Train's auc: 0.843952 Evaluation's auc: 0.825581 [341] Train's auc: 0.844016 Evaluation's auc: 0.825612 [342] Train's auc: 0.844051 Evaluation's auc: 0.825645 [343] Train's auc: 0.844095 Evaluation's auc: 0.825667 [344] Train's auc: 0.84412 Evaluation's auc: 0.825687 [345] Train's auc: 0.844164 Evaluation's auc: 0.825719 [346] Train's auc: 0.844234 Evaluation's auc: 0.825792 [347] Train's auc: 0.844297 Evaluation's auc: 0.825858 [348] Train's auc: 0.844359 Evaluation's auc: 0.825895 [349] Train's auc: 0.844405 Evaluation's auc: 0.825935 [350] Train's auc: 0.844444 Evaluation's auc: 0.825973 [351] Train's auc: 0.844488 Evaluation's auc: 0.825976 [352] Train's auc: 0.844515 Evaluation's auc: 0.825975 [353] Train's auc: 0.844552 Evaluation's auc: 0.826 [354] Train's auc: 0.844598 Evaluation's auc: 0.82601 [355] Train's auc: 0.844633 Evaluation's auc: 0.826045 [356] Train's auc: 0.84467 Evaluation's auc: 0.826077 [357] Train's auc: 0.844705 Evaluation's auc: 0.826096 [358] Train's auc: 0.844764 Evaluation's auc: 0.826126 [359] Train's auc: 0.844824 Evaluation's auc: 0.826182 [360] Train's auc: 0.844849 Evaluation's auc: 0.826199 [361] Train's auc: 0.844884 Evaluation's auc: 0.826194 [362] Train's auc: 0.844932 Evaluation's auc: 0.826238 [363] Train's auc: 0.844963 Evaluation's auc: 0.826247 [364] Train's auc: 0.845015 Evaluation's auc: 0.826277 [365] Train's auc: 0.845078 Evaluation's auc: 0.826343 [366] Train's auc: 0.845135 Evaluation's auc: 0.826373 [367] Train's auc: 0.845165 Evaluation's auc: 0.826385 [368] Train's auc: 0.845206 Evaluation's auc: 0.826393 [369] Train's auc: 0.845234 Evaluation's auc: 0.826406 [370] Train's auc: 0.845273 Evaluation's auc: 0.826444 [371] Train's auc: 0.845312 Evaluation's auc: 0.826468 [372] Train's auc: 0.845377 Evaluation's auc: 0.826541 [373] Train's auc: 0.845423 Evaluation's auc: 0.826588 [374] Train's auc: 0.845457 Evaluation's auc: 0.826624 [375] Train's auc: 0.845492 Evaluation's auc: 0.826628 [376] Train's auc: 0.845526 Evaluation's auc: 0.826643 [377] Train's auc: 0.845562 Evaluation's auc: 0.826638 [378] Train's auc: 0.845593 Evaluation's auc: 0.826653 [379] Train's auc: 0.845644 Evaluation's auc: 0.826692 [380] Train's auc: 0.845688 Evaluation's auc: 0.826738 [381] Train's auc: 0.845736 Evaluation's auc: 0.826765 [382] Train's auc: 0.845772 Evaluation's auc: 0.826776 [383] Train's auc: 0.845822 Evaluation's auc: 0.82677 [384] Train's auc: 0.845852 Evaluation's auc: 0.826772 [385] Train's auc: 0.845879 Evaluation's auc: 0.826786 [386] Train's auc: 0.845903 Evaluation's auc: 0.82681 [387] Train's auc: 0.845942 Evaluation's auc: 0.826845 [388] Train's auc: 0.845994 Evaluation's auc: 0.8269 [389] Train's auc: 0.846031 Evaluation's auc: 0.826905 [390] Train's auc: 0.846068 Evaluation's auc: 0.826926 [391] Train's auc: 0.846124 Evaluation's auc: 0.82699 [392] Train's auc: 0.84616 Evaluation's auc: 0.827006 [393] Train's auc: 0.846193 Evaluation's auc: 0.827026 [394] Train's auc: 0.846218 Evaluation's auc: 0.827044 [395] Train's auc: 0.846253 Evaluation's auc: 0.827069 [396] Train's auc: 0.846266 Evaluation's auc: 0.827066 [397] Train's auc: 0.846322 Evaluation's auc: 0.827098 [398] Train's auc: 0.846359 Evaluation's auc: 0.827118 [399] Train's auc: 0.846388 Evaluation's auc: 0.827122 [400] Train's auc: 0.846425 Evaluation's auc: 0.827162 [401] Train's auc: 0.846455 Evaluation's auc: 0.827169 [402] Train's auc: 0.84649 Evaluation's auc: 0.827172 [403] Train's auc: 0.846536 Evaluation's auc: 0.827201 [404] Train's auc: 0.846564 Evaluation's auc: 0.827204 [405] Train's auc: 0.846606 Evaluation's auc: 0.827231 [406] Train's auc: 0.84664 Evaluation's auc: 0.827246 [407] Train's auc: 0.846688 Evaluation's auc: 0.82728 [408] Train's auc: 0.846723 Evaluation's auc: 0.827313 [409] Train's auc: 0.846751 Evaluation's auc: 0.827327 [410] Train's auc: 0.846789 Evaluation's auc: 0.827364 [411] Train's auc: 0.846828 Evaluation's auc: 0.827383 [412] Train's auc: 0.846872 Evaluation's auc: 0.827407 [413] Train's auc: 0.846902 Evaluation's auc: 0.827408 [414] Train's auc: 0.846956 Evaluation's auc: 0.827452 [415] Train's auc: 0.846998 Evaluation's auc: 0.827461 [416] Train's auc: 0.847039 Evaluation's auc: 0.82748 [417] Train's auc: 0.847072 Evaluation's auc: 0.827486 [418] Train's auc: 0.847107 Evaluation's auc: 0.827499 [419] Train's auc: 0.847133 Evaluation's auc: 0.82751 [420] Train's auc: 0.847195 Evaluation's auc: 0.827545 [421] Train's auc: 0.847218 Evaluation's auc: 0.827564 [422] Train's auc: 0.847257 Evaluation's auc: 0.827585 [423] Train's auc: 0.847296 Evaluation's auc: 0.82758 [424] Train's auc: 0.847324 Evaluation's auc: 0.827611 [425] Train's auc: 0.847351 Evaluation's auc: 0.827613 [426] Train's auc: 0.847396 Evaluation's auc: 0.827641 [427] Train's auc: 0.847437 Evaluation's auc: 0.827672 [428] Train's auc: 0.847467 Evaluation's auc: 0.827671 [429] Train's auc: 0.847509 Evaluation's auc: 0.827709 [430] Train's auc: 0.847557 Evaluation's auc: 0.827735 [431] Train's auc: 0.847594 Evaluation's auc: 0.827749 [432] Train's auc: 0.847627 Evaluation's auc: 0.827768 [433] Train's auc: 0.847662 Evaluation's auc: 0.827762 [434] Train's auc: 0.84769 Evaluation's auc: 0.827774 [435] Train's auc: 0.847728 Evaluation's auc: 0.827793 [436] Train's auc: 0.847765 Evaluation's auc: 0.827828 [437] Train's auc: 0.847793 Evaluation's auc: 0.827847 [438] Train's auc: 0.847848 Evaluation's auc: 0.827904 [439] Train's auc: 0.847897 Evaluation's auc: 0.827934 [440] Train's auc: 0.847932 Evaluation's auc: 0.827943 [441] Train's auc: 0.847992 Evaluation's auc: 0.827981 [442] Train's auc: 0.848017 Evaluation's auc: 0.827985 [443] Train's auc: 0.848044 Evaluation's auc: 0.827995 [444] Train's auc: 0.848089 Evaluation's auc: 0.828022 [445] Train's auc: 0.848119 Evaluation's auc: 0.828039 [446] Train's auc: 0.848145 Evaluation's auc: 0.828051 [447] Train's auc: 0.848174 Evaluation's auc: 0.828068 [448] Train's auc: 0.848207 Evaluation's auc: 0.828097 [449] Train's auc: 0.848223 Evaluation's auc: 0.828106 [450] Train's auc: 0.848255 Evaluation's auc: 0.828112 [451] Train's auc: 0.848281 Evaluation's auc: 0.828134 [452] Train's auc: 0.848311 Evaluation's auc: 0.828162 [453] Train's auc: 0.848341 Evaluation's auc: 0.828175 [454] Train's auc: 0.848369 Evaluation's auc: 0.828181 [455] Train's auc: 0.848399 Evaluation's auc: 0.828182 [456] Train's auc: 0.848422 Evaluation's auc: 0.828187 [457] Train's auc: 0.848453 Evaluation's auc: 0.82819 [458] Train's auc: 0.848516 Evaluation's auc: 0.828245 [459] Train's auc: 0.848547 Evaluation's auc: 0.828267 [460] Train's auc: 0.848579 Evaluation's auc: 0.828271 [461] Train's auc: 0.848626 Evaluation's auc: 0.828328 [462] Train's auc: 0.848661 Evaluation's auc: 0.828333 [463] Train's auc: 0.848683 Evaluation's auc: 0.828336 [464] Train's auc: 0.848727 Evaluation's auc: 0.828345 [465] Train's auc: 0.848757 Evaluation's auc: 0.828375 [466] Train's auc: 0.848793 Evaluation's auc: 0.828393 [467] Train's auc: 0.848833 Evaluation's auc: 0.828424 [468] Train's auc: 0.848865 Evaluation's auc: 0.828442 [469] Train's auc: 0.84889 Evaluation's auc: 0.828438 [470] Train's auc: 0.848935 Evaluation's auc: 0.82847 [471] Train's auc: 0.848957 Evaluation's auc: 0.828471 [472] Train's auc: 0.848987 Evaluation's auc: 0.828504 [473] Train's auc: 0.849028 Evaluation's auc: 0.828541 [474] Train's auc: 0.849074 Evaluation's auc: 0.8286 [475] Train's auc: 0.849115 Evaluation's auc: 0.82863 [476] Train's auc: 0.849147 Evaluation's auc: 0.828648 [477] Train's auc: 0.849178 Evaluation's auc: 0.828659 [478] Train's auc: 0.849211 Evaluation's auc: 0.828677 [479] Train's auc: 0.849237 Evaluation's auc: 0.828682 [480] Train's auc: 0.849269 Evaluation's auc: 0.828689 [481] Train's auc: 0.8493 Evaluation's auc: 0.828727 [482] Train's auc: 0.849334 Evaluation's auc: 0.828743 [483] Train's auc: 0.84935 Evaluation's auc: 0.828737 [484] Train's auc: 0.849396 Evaluation's auc: 0.82877 [485] Train's auc: 0.849437 Evaluation's auc: 0.828804 [486] Train's auc: 0.849464 Evaluation's auc: 0.828821 [487] Train's auc: 0.849504 Evaluation's auc: 0.828844 [488] Train's auc: 0.849534 Evaluation's auc: 0.828865 [489] Train's auc: 0.849568 Evaluation's auc: 0.828899 [490] Train's auc: 0.849589 Evaluation's auc: 0.82891 [491] Train's auc: 0.849627 Evaluation's auc: 0.828943 [492] Train's auc: 0.849647 Evaluation's auc: 0.828951 [493] Train's auc: 0.849708 Evaluation's auc: 0.829001 [494] Train's auc: 0.849762 Evaluation's auc: 0.829049 [495] Train's auc: 0.849785 Evaluation's auc: 0.829059 [496] Train's auc: 0.849839 Evaluation's auc: 0.829109 [497] Train's auc: 0.849878 Evaluation's auc: 0.829113 [498] Train's auc: 0.849912 Evaluation's auc: 0.829131 [499] Train's auc: 0.849952 Evaluation's auc: 0.829137 [500] Train's auc: 0.84999 Evaluation's auc: 0.829144 [501] Train's auc: 0.85002 Evaluation's auc: 0.829148 [502] Train's auc: 0.85006 Evaluation's auc: 0.829177 [503] Train's auc: 0.850094 Evaluation's auc: 0.82918 [504] Train's auc: 0.85013 Evaluation's auc: 0.829196 [505] Train's auc: 0.850171 Evaluation's auc: 0.829201 [506] Train's auc: 0.850204 Evaluation's auc: 0.82923 [507] Train's auc: 0.85024 Evaluation's auc: 0.829255 [508] Train's auc: 0.850274 Evaluation's auc: 0.829248 [509] Train's auc: 0.850306 Evaluation's auc: 0.829278 [510] Train's auc: 0.85034 Evaluation's auc: 0.829292 [511] Train's auc: 0.850385 Evaluation's auc: 0.829324 [512] Train's auc: 0.850405 Evaluation's auc: 0.829325 [513] Train's auc: 0.850443 Evaluation's auc: 0.829343 [514] Train's auc: 0.850489 Evaluation's auc: 0.829385 [515] Train's auc: 0.850525 Evaluation's auc: 0.829389 [516] Train's auc: 0.850573 Evaluation's auc: 0.829425 [517] Train's auc: 0.850602 Evaluation's auc: 0.82944 [518] Train's auc: 0.850634 Evaluation's auc: 0.829465 [519] Train's auc: 0.850675 Evaluation's auc: 0.829487 [520] Train's auc: 0.850698 Evaluation's auc: 0.82951 [521] Train's auc: 0.850729 Evaluation's auc: 0.829516 [522] Train's auc: 0.850778 Evaluation's auc: 0.829539 [523] Train's auc: 0.85081 Evaluation's auc: 0.829541 [524] Train's auc: 0.850849 Evaluation's auc: 0.829569 [525] Train's auc: 0.850881 Evaluation's auc: 0.829582 [526] Train's auc: 0.850904 Evaluation's auc: 0.829602 [527] Train's auc: 0.850939 Evaluation's auc: 0.82961 [528] Train's auc: 0.850965 Evaluation's auc: 0.829613 [529] Train's auc: 0.851014 Evaluation's auc: 0.829654 [530] Train's auc: 0.851051 Evaluation's auc: 0.829668 [531] Train's auc: 0.851069 Evaluation's auc: 0.82967 [532] Train's auc: 0.851104 Evaluation's auc: 0.82967 [533] Train's auc: 0.851133 Evaluation's auc: 0.829693 [534] Train's auc: 0.851149 Evaluation's auc: 0.829687 [535] Train's auc: 0.85119 Evaluation's auc: 0.829728 [536] Train's auc: 0.851221 Evaluation's auc: 0.829737 [537] Train's auc: 0.851256 Evaluation's auc: 0.829763 [538] Train's auc: 0.851278 Evaluation's auc: 0.829765 [539] Train's auc: 0.851309 Evaluation's auc: 0.829779 [540] Train's auc: 0.851351 Evaluation's auc: 0.829815 [541] Train's auc: 0.851402 Evaluation's auc: 0.829854 [542] Train's auc: 0.851426 Evaluation's auc: 0.829854 [543] Train's auc: 0.851452 Evaluation's auc: 0.829856 [544] Train's auc: 0.851489 Evaluation's auc: 0.829887 [545] Train's auc: 0.851526 Evaluation's auc: 0.829922 [546] Train's auc: 0.851563 Evaluation's auc: 0.829952 [547] Train's auc: 0.851617 Evaluation's auc: 0.830004 [548] Train's auc: 0.851643 Evaluation's auc: 0.83 [549] Train's auc: 0.85166 Evaluation's auc: 0.829998 [550] Train's auc: 0.851686 Evaluation's auc: 0.830001 [551] Train's auc: 0.851727 Evaluation's auc: 0.830029 [552] Train's auc: 0.851765 Evaluation's auc: 0.830061 [553] Train's auc: 0.851807 Evaluation's auc: 0.830095 [554] Train's auc: 0.851839 Evaluation's auc: 0.830102 [555] Train's auc: 0.851869 Evaluation's auc: 0.83011 [556] Train's auc: 0.85191 Evaluation's auc: 0.830141 [557] Train's auc: 0.851938 Evaluation's auc: 0.83014 [558] Train's auc: 0.851978 Evaluation's auc: 0.830153 [559] Train's auc: 0.852013 Evaluation's auc: 0.830165 [560] Train's auc: 0.852033 Evaluation's auc: 0.830181 [561] Train's auc: 0.852088 Evaluation's auc: 0.830233 [562] Train's auc: 0.852113 Evaluation's auc: 0.830239 [563] Train's auc: 0.852136 Evaluation's auc: 0.830243 [564] Train's auc: 0.852155 Evaluation's auc: 0.830259 [565] Train's auc: 0.852185 Evaluation's auc: 0.830277 [566] Train's auc: 0.852213 Evaluation's auc: 0.830293 [567] Train's auc: 0.852239 Evaluation's auc: 0.830302 [568] Train's auc: 0.852267 Evaluation's auc: 0.830329 [569] Train's auc: 0.852307 Evaluation's auc: 0.830341 [570] Train's auc: 0.852336 Evaluation's auc: 0.830349 [571] Train's auc: 0.852373 Evaluation's auc: 0.830364 [572] Train's auc: 0.852392 Evaluation's auc: 0.830374 [573] Train's auc: 0.852418 Evaluation's auc: 0.830384 [574] Train's auc: 0.852463 Evaluation's auc: 0.830395 [575] Train's auc: 0.852482 Evaluation's auc: 0.830403 [576] Train's auc: 0.852528 Evaluation's auc: 0.830418 [577] Train's auc: 0.852559 Evaluation's auc: 0.830424 [578] Train's auc: 0.852584 Evaluation's auc: 0.830417 [579] Train's auc: 0.852616 Evaluation's auc: 0.830438 [580] Train's auc: 0.852638 Evaluation's auc: 0.83045 [581] Train's auc: 0.852671 Evaluation's auc: 0.830481 [582] Train's auc: 0.85269 Evaluation's auc: 0.830489 [583] Train's auc: 0.852713 Evaluation's auc: 0.830514 [584] Train's auc: 0.852744 Evaluation's auc: 0.830529 [585] Train's auc: 0.852784 Evaluation's auc: 0.830576 [586] Train's auc: 0.85281 Evaluation's auc: 0.830591 [587] Train's auc: 0.852837 Evaluation's auc: 0.830595 [588] Train's auc: 0.852869 Evaluation's auc: 0.83061 [589] Train's auc: 0.852906 Evaluation's auc: 0.830644 [590] Train's auc: 0.85294 Evaluation's auc: 0.830636 [591] Train's auc: 0.852958 Evaluation's auc: 0.830622 [592] Train's auc: 0.853001 Evaluation's auc: 0.830657 [593] Train's auc: 0.853022 Evaluation's auc: 0.830641 [594] Train's auc: 0.853044 Evaluation's auc: 0.830635 [595] Train's auc: 0.853075 Evaluation's auc: 0.830653 [596] Train's auc: 0.853096 Evaluation's auc: 0.830665 [597] Train's auc: 0.853118 Evaluation's auc: 0.830666 [598] Train's auc: 0.853142 Evaluation's auc: 0.830666 [599] Train's auc: 0.853167 Evaluation's auc: 0.830674 [600] Train's auc: 0.853195 Evaluation's auc: 0.830689 [601] Train's auc: 0.853233 Evaluation's auc: 0.830708 [602] Train's auc: 0.853265 Evaluation's auc: 0.830711 [603] Train's auc: 0.853299 Evaluation's auc: 0.830746 [604] Train's auc: 0.85333 Evaluation's auc: 0.830749 [605] Train's auc: 0.853367 Evaluation's auc: 0.830772 [606] Train's auc: 0.853421 Evaluation's auc: 0.83081 [607] Train's auc: 0.853447 Evaluation's auc: 0.830822 [608] Train's auc: 0.853475 Evaluation's auc: 0.830828 [609] Train's auc: 0.853515 Evaluation's auc: 0.830837 [610] Train's auc: 0.853548 Evaluation's auc: 0.830849 [611] Train's auc: 0.853576 Evaluation's auc: 0.830872 [612] Train's auc: 0.853609 Evaluation's auc: 0.830903 [613] Train's auc: 0.853631 Evaluation's auc: 0.830906 [614] Train's auc: 0.853657 Evaluation's auc: 0.830895 [615] Train's auc: 0.853683 Evaluation's auc: 0.830904 [616] Train's auc: 0.853724 Evaluation's auc: 0.830954 [617] Train's auc: 0.853736 Evaluation's auc: 0.830955 [618] Train's auc: 0.853758 Evaluation's auc: 0.830949 [619] Train's auc: 0.853786 Evaluation's auc: 0.830956 [620] Train's auc: 0.853816 Evaluation's auc: 0.830955 [621] Train's auc: 0.853855 Evaluation's auc: 0.831002 [622] Train's auc: 0.853874 Evaluation's auc: 0.831011 [623] Train's auc: 0.853906 Evaluation's auc: 0.831023 [624] Train's auc: 0.85394 Evaluation's auc: 0.831028 [625] Train's auc: 0.853966 Evaluation's auc: 0.831023 [626] Train's auc: 0.854002 Evaluation's auc: 0.831047 [627] Train's auc: 0.854028 Evaluation's auc: 0.831053 [628] Train's auc: 0.854064 Evaluation's auc: 0.831071 [629] Train's auc: 0.854097 Evaluation's auc: 0.831121 [630] Train's auc: 0.854131 Evaluation's auc: 0.831128 [631] Train's auc: 0.854149 Evaluation's auc: 0.831125 [632] Train's auc: 0.854187 Evaluation's auc: 0.831153 [633] Train's auc: 0.854231 Evaluation's auc: 0.831189 [634] Train's auc: 0.854272 Evaluation's auc: 0.831237 [635] Train's auc: 0.854299 Evaluation's auc: 0.831236 [636] Train's auc: 0.854319 Evaluation's auc: 0.831235 [637] Train's auc: 0.854351 Evaluation's auc: 0.831244 [638] Train's auc: 0.854382 Evaluation's auc: 0.831273 [639] Train's auc: 0.854414 Evaluation's auc: 0.831297 [640] Train's auc: 0.854444 Evaluation's auc: 0.831315 [641] Train's auc: 0.854467 Evaluation's auc: 0.831322 [642] Train's auc: 0.854505 Evaluation's auc: 0.831355 [643] Train's auc: 0.854523 Evaluation's auc: 0.83136 [644] Train's auc: 0.854552 Evaluation's auc: 0.831377 [645] Train's auc: 0.85458 Evaluation's auc: 0.831383 [646] Train's auc: 0.854606 Evaluation's auc: 0.831379 [647] Train's auc: 0.854634 Evaluation's auc: 0.831421 [648] Train's auc: 0.854673 Evaluation's auc: 0.831439 [649] Train's auc: 0.854697 Evaluation's auc: 0.831463 [650] Train's auc: 0.854729 Evaluation's auc: 0.831478 [651] Train's auc: 0.854751 Evaluation's auc: 0.831484 [652] Train's auc: 0.854793 Evaluation's auc: 0.831524 [653] Train's auc: 0.85482 Evaluation's auc: 0.831541 [654] Train's auc: 0.854849 Evaluation's auc: 0.831547 [655] Train's auc: 0.854882 Evaluation's auc: 0.831532 [656] Train's auc: 0.854915 Evaluation's auc: 0.831537 [657] Train's auc: 0.854948 Evaluation's auc: 0.831543 [658] Train's auc: 0.854971 Evaluation's auc: 0.831543 [659] Train's auc: 0.855012 Evaluation's auc: 0.831578 [660] Train's auc: 0.855043 Evaluation's auc: 0.831609 [661] Train's auc: 0.855065 Evaluation's auc: 0.831605 [662] Train's auc: 0.855092 Evaluation's auc: 0.831609 [663] Train's auc: 0.855116 Evaluation's auc: 0.831616 [664] Train's auc: 0.855136 Evaluation's auc: 0.831618 [665] Train's auc: 0.855152 Evaluation's auc: 0.831612 [666] Train's auc: 0.855187 Evaluation's auc: 0.831645 [667] Train's auc: 0.855218 Evaluation's auc: 0.831648 [668] Train's auc: 0.855237 Evaluation's auc: 0.83165 [669] Train's auc: 0.855259 Evaluation's auc: 0.831674 [670] Train's auc: 0.855284 Evaluation's auc: 0.831682 [671] Train's auc: 0.85531 Evaluation's auc: 0.831696 [672] Train's auc: 0.855345 Evaluation's auc: 0.831709 [673] Train's auc: 0.855368 Evaluation's auc: 0.831724 [674] Train's auc: 0.8554 Evaluation's auc: 0.831764 [675] Train's auc: 0.855435 Evaluation's auc: 0.831799 [676] Train's auc: 0.85546 Evaluation's auc: 0.831815 [677] Train's auc: 0.855481 Evaluation's auc: 0.831803 [678] Train's auc: 0.855505 Evaluation's auc: 0.831803 [679] Train's auc: 0.855523 Evaluation's auc: 0.831798 [680] Train's auc: 0.855553 Evaluation's auc: 0.831815 [681] Train's auc: 0.855588 Evaluation's auc: 0.831832 [682] Train's auc: 0.855621 Evaluation's auc: 0.83186 [683] Train's auc: 0.855641 Evaluation's auc: 0.831869 [684] Train's auc: 0.85567 Evaluation's auc: 0.831904 [685] Train's auc: 0.855699 Evaluation's auc: 0.83192 [686] Train's auc: 0.855722 Evaluation's auc: 0.831941 [687] Train's auc: 0.85574 Evaluation's auc: 0.831942 [688] Train's auc: 0.855774 Evaluation's auc: 0.831971 [689] Train's auc: 0.855788 Evaluation's auc: 0.831981 [690] Train's auc: 0.855814 Evaluation's auc: 0.831991 [691] Train's auc: 0.855837 Evaluation's auc: 0.832016 [692] Train's auc: 0.85586 Evaluation's auc: 0.832017 [693] Train's auc: 0.855885 Evaluation's auc: 0.83204 [694] Train's auc: 0.855903 Evaluation's auc: 0.832047 [695] Train's auc: 0.855934 Evaluation's auc: 0.832041 [696] Train's auc: 0.855953 Evaluation's auc: 0.832049 [697] Train's auc: 0.855978 Evaluation's auc: 0.832065 [698] Train's auc: 0.855996 Evaluation's auc: 0.832061 [699] Train's auc: 0.856032 Evaluation's auc: 0.832085 [700] Train's auc: 0.856049 Evaluation's auc: 0.832095 [701] Train's auc: 0.85608 Evaluation's auc: 0.832106 [702] Train's auc: 0.856105 Evaluation's auc: 0.832105 [703] Train's auc: 0.856126 Evaluation's auc: 0.832101 [704] Train's auc: 0.856153 Evaluation's auc: 0.832109 [705] Train's auc: 0.856179 Evaluation's auc: 0.832144 [706] Train's auc: 0.856215 Evaluation's auc: 0.832171 [707] Train's auc: 0.856231 Evaluation's auc: 0.832181 [708] Train's auc: 0.856247 Evaluation's auc: 0.832179 [709] Train's auc: 0.856277 Evaluation's auc: 0.83219 [710] Train's auc: 0.856305 Evaluation's auc: 0.832208 [711] Train's auc: 0.85634 Evaluation's auc: 0.832236 [712] Train's auc: 0.856368 Evaluation's auc: 0.832229 [713] Train's auc: 0.856398 Evaluation's auc: 0.83223 [714] Train's auc: 0.856418 Evaluation's auc: 0.832261 [715] Train's auc: 0.85644 Evaluation's auc: 0.832278 [716] Train's auc: 0.856474 Evaluation's auc: 0.832292 [717] Train's auc: 0.856494 Evaluation's auc: 0.832282 [718] Train's auc: 0.856526 Evaluation's auc: 0.83228 [719] Train's auc: 0.856551 Evaluation's auc: 0.832281 [720] Train's auc: 0.856574 Evaluation's auc: 0.832284 [721] Train's auc: 0.85659 Evaluation's auc: 0.832281 [722] Train's auc: 0.856622 Evaluation's auc: 0.832304 [723] Train's auc: 0.856636 Evaluation's auc: 0.8323 [724] Train's auc: 0.856651 Evaluation's auc: 0.832302 [725] Train's auc: 0.856679 Evaluation's auc: 0.832315 [726] Train's auc: 0.856694 Evaluation's auc: 0.832323 [727] Train's auc: 0.85673 Evaluation's auc: 0.832365 [728] Train's auc: 0.856755 Evaluation's auc: 0.832365 [729] Train's auc: 0.856772 Evaluation's auc: 0.832349 [730] Train's auc: 0.856797 Evaluation's auc: 0.832357 [731] Train's auc: 0.856829 Evaluation's auc: 0.832394 [732] Train's auc: 0.856846 Evaluation's auc: 0.832404 [733] Train's auc: 0.856871 Evaluation's auc: 0.832425 [734] Train's auc: 0.856897 Evaluation's auc: 0.832419 [735] Train's auc: 0.856922 Evaluation's auc: 0.832431 [736] Train's auc: 0.856951 Evaluation's auc: 0.832457 [737] Train's auc: 0.856974 Evaluation's auc: 0.832469 [738] Train's auc: 0.857003 Evaluation's auc: 0.832496 [739] Train's auc: 0.857031 Evaluation's auc: 0.832518 [740] Train's auc: 0.857059 Evaluation's auc: 0.832523 [741] Train's auc: 0.857097 Evaluation's auc: 0.832558 [742] Train's auc: 0.857124 Evaluation's auc: 0.832564 [743] Train's auc: 0.857145 Evaluation's auc: 0.832581 [744] Train's auc: 0.857169 Evaluation's auc: 0.832576 [745] Train's auc: 0.857182 Evaluation's auc: 0.832579 [746] Train's auc: 0.85722 Evaluation's auc: 0.832577 [747] Train's auc: 0.857238 Evaluation's auc: 0.832569 [748] Train's auc: 0.857262 Evaluation's auc: 0.832582 [749] Train's auc: 0.857279 Evaluation's auc: 0.832595 [750] Train's auc: 0.857303 Evaluation's auc: 0.832618 [751] Train's auc: 0.857325 Evaluation's auc: 0.832623 [752] Train's auc: 0.85735 Evaluation's auc: 0.832657 [753] Train's auc: 0.85737 Evaluation's auc: 0.832667 [754] Train's auc: 0.857392 Evaluation's auc: 0.832683 [755] Train's auc: 0.857409 Evaluation's auc: 0.832677 [756] Train's auc: 0.857437 Evaluation's auc: 0.832681 [757] Train's auc: 0.857458 Evaluation's auc: 0.832684 [758] Train's auc: 0.85749 Evaluation's auc: 0.83267 [759] Train's auc: 0.857503 Evaluation's auc: 0.832683 [760] Train's auc: 0.857516 Evaluation's auc: 0.83267 [761] Train's auc: 0.857543 Evaluation's auc: 0.832674 [762] Train's auc: 0.857549 Evaluation's auc: 0.832676 [763] Train's auc: 0.857577 Evaluation's auc: 0.832706 [764] Train's auc: 0.857605 Evaluation's auc: 0.832731 [765] Train's auc: 0.857622 Evaluation's auc: 0.832746 [766] Train's auc: 0.857651 Evaluation's auc: 0.832759 [767] Train's auc: 0.85767 Evaluation's auc: 0.832759 [768] Train's auc: 0.857691 Evaluation's auc: 0.832764 [769] Train's auc: 0.857714 Evaluation's auc: 0.832771 [770] Train's auc: 0.85773 Evaluation's auc: 0.832765 [771] Train's auc: 0.85775 Evaluation's auc: 0.832771 [772] Train's auc: 0.857769 Evaluation's auc: 0.832768 [773] Train's auc: 0.85778 Evaluation's auc: 0.832764 [774] Train's auc: 0.857811 Evaluation's auc: 0.83279 [775] Train's auc: 0.857834 Evaluation's auc: 0.832806 [776] Train's auc: 0.857854 Evaluation's auc: 0.832833 [777] Train's auc: 0.857879 Evaluation's auc: 0.83285 [778] Train's auc: 0.857901 Evaluation's auc: 0.832858 [779] Train's auc: 0.857917 Evaluation's auc: 0.832849 [780] Train's auc: 0.857938 Evaluation's auc: 0.832866 [781] Train's auc: 0.85796 Evaluation's auc: 0.83288 [782] Train's auc: 0.857983 Evaluation's auc: 0.832881 [783] Train's auc: 0.858004 Evaluation's auc: 0.832883 [784] Train's auc: 0.858021 Evaluation's auc: 0.832882 [785] Train's auc: 0.858047 Evaluation's auc: 0.8329 [786] Train's auc: 0.858073 Evaluation's auc: 0.832897 [787] Train's auc: 0.858091 Evaluation's auc: 0.832913 [788] Train's auc: 0.858107 Evaluation's auc: 0.83291 [789] Train's auc: 0.858132 Evaluation's auc: 0.832931 [790] Train's auc: 0.858165 Evaluation's auc: 0.832955 [791] Train's auc: 0.858187 Evaluation's auc: 0.832956 [792] Train's auc: 0.858205 Evaluation's auc: 0.832973 [793] Train's auc: 0.858225 Evaluation's auc: 0.832986 [794] Train's auc: 0.858245 Evaluation's auc: 0.832981 [795] Train's auc: 0.858274 Evaluation's auc: 0.833 [796] Train's auc: 0.8583 Evaluation's auc: 0.833013 [797] Train's auc: 0.858322 Evaluation's auc: 0.83304 [798] Train's auc: 0.858346 Evaluation's auc: 0.833045 [799] Train's auc: 0.858369 Evaluation's auc: 0.833065 [800] Train's auc: 0.858389 Evaluation's auc: 0.833066 [801] Train's auc: 0.858408 Evaluation's auc: 0.833068 [802] Train's auc: 0.858433 Evaluation's auc: 0.833105 [803] Train's auc: 0.858459 Evaluation's auc: 0.833114 [804] Train's auc: 0.858489 Evaluation's auc: 0.83311 [805] Train's auc: 0.858523 Evaluation's auc: 0.833134 [806] Train's auc: 0.858553 Evaluation's auc: 0.833161 [807] Train's auc: 0.858574 Evaluation's auc: 0.833154 [808] Train's auc: 0.858607 Evaluation's auc: 0.833164 [809] Train's auc: 0.858632 Evaluation's auc: 0.833158 [810] Train's auc: 0.858651 Evaluation's auc: 0.833169 [811] Train's auc: 0.85867 Evaluation's auc: 0.833166 [812] Train's auc: 0.858694 Evaluation's auc: 0.833182 [813] Train's auc: 0.858718 Evaluation's auc: 0.833192 [814] Train's auc: 0.858741 Evaluation's auc: 0.833207 [815] Train's auc: 0.858763 Evaluation's auc: 0.833203 [816] Train's auc: 0.858791 Evaluation's auc: 0.833221 [817] Train's auc: 0.858805 Evaluation's auc: 0.833224 [818] Train's auc: 0.858826 Evaluation's auc: 0.83323 [819] Train's auc: 0.858844 Evaluation's auc: 0.833238 [820] Train's auc: 0.858863 Evaluation's auc: 0.83323 [821] Train's auc: 0.858891 Evaluation's auc: 0.833256 [822] Train's auc: 0.858905 Evaluation's auc: 0.83327 [823] Train's auc: 0.858924 Evaluation's auc: 0.83327 [824] Train's auc: 0.858941 Evaluation's auc: 0.833275 [825] Train's auc: 0.858959 Evaluation's auc: 0.833293 [826] Train's auc: 0.858975 Evaluation's auc: 0.833271 [827] Train's auc: 0.859006 Evaluation's auc: 0.833287 [828] Train's auc: 0.859029 Evaluation's auc: 0.833285 [829] Train's auc: 0.85905 Evaluation's auc: 0.833298 [830] Train's auc: 0.859077 Evaluation's auc: 0.833305 [831] Train's auc: 0.859103 Evaluation's auc: 0.833321 [832] Train's auc: 0.859124 Evaluation's auc: 0.833324 [833] Train's auc: 0.859148 Evaluation's auc: 0.833318 [834] Train's auc: 0.85918 Evaluation's auc: 0.833344 [835] Train's auc: 0.859204 Evaluation's auc: 0.833345 [836] Train's auc: 0.859225 Evaluation's auc: 0.833365 [837] Train's auc: 0.859244 Evaluation's auc: 0.833372 [838] Train's auc: 0.859257 Evaluation's auc: 0.833369 [839] Train's auc: 0.859284 Evaluation's auc: 0.83338 [840] Train's auc: 0.859306 Evaluation's auc: 0.833378 [841] Train's auc: 0.859323 Evaluation's auc: 0.833398 [842] Train's auc: 0.859347 Evaluation's auc: 0.833418 [843] Train's auc: 0.859372 Evaluation's auc: 0.833428 [844] Train's auc: 0.859397 Evaluation's auc: 0.833427 [845] Train's auc: 0.859419 Evaluation's auc: 0.833437 [846] Train's auc: 0.859456 Evaluation's auc: 0.833464 [847] Train's auc: 0.859473 Evaluation's auc: 0.833475 [848] Train's auc: 0.859502 Evaluation's auc: 0.833511 [849] Train's auc: 0.859522 Evaluation's auc: 0.83351 [850] Train's auc: 0.859538 Evaluation's auc: 0.833509 [851] Train's auc: 0.859564 Evaluation's auc: 0.833508 [852] Train's auc: 0.859595 Evaluation's auc: 0.833533 [853] Train's auc: 0.859614 Evaluation's auc: 0.83353 [854] Train's auc: 0.85963 Evaluation's auc: 0.833538 [855] Train's auc: 0.859651 Evaluation's auc: 0.833553 [856] Train's auc: 0.859678 Evaluation's auc: 0.833553 [857] Train's auc: 0.859703 Evaluation's auc: 0.833561 [858] Train's auc: 0.859719 Evaluation's auc: 0.833552 [859] Train's auc: 0.859737 Evaluation's auc: 0.83355 [860] Train's auc: 0.859764 Evaluation's auc: 0.83356 [861] Train's auc: 0.859792 Evaluation's auc: 0.833584 [862] Train's auc: 0.859809 Evaluation's auc: 0.833577 [863] Train's auc: 0.859841 Evaluation's auc: 0.8336 [864] Train's auc: 0.859863 Evaluation's auc: 0.833598 [865] Train's auc: 0.85988 Evaluation's auc: 0.833603 [866] Train's auc: 0.859899 Evaluation's auc: 0.83361 [867] Train's auc: 0.859922 Evaluation's auc: 0.833624 [868] Train's auc: 0.859943 Evaluation's auc: 0.833619 [869] Train's auc: 0.859966 Evaluation's auc: 0.833629 [870] Train's auc: 0.859991 Evaluation's auc: 0.833626 [871] Train's auc: 0.860005 Evaluation's auc: 0.833633 [872] Train's auc: 0.860031 Evaluation's auc: 0.833651 [873] Train's auc: 0.860045 Evaluation's auc: 0.83366 [874] Train's auc: 0.860072 Evaluation's auc: 0.833685 [875] Train's auc: 0.860087 Evaluation's auc: 0.833695 [876] Train's auc: 0.860111 Evaluation's auc: 0.83369 [877] Train's auc: 0.86013 Evaluation's auc: 0.833707 [878] Train's auc: 0.860154 Evaluation's auc: 0.833707 [879] Train's auc: 0.860174 Evaluation's auc: 0.833721 [880] Train's auc: 0.860186 Evaluation's auc: 0.833717 [881] Train's auc: 0.8602 Evaluation's auc: 0.833718 [882] Train's auc: 0.860225 Evaluation's auc: 0.833734 [883] Train's auc: 0.860237 Evaluation's auc: 0.83375 [884] Train's auc: 0.860259 Evaluation's auc: 0.833769 [885] Train's auc: 0.860282 Evaluation's auc: 0.833775 [886] Train's auc: 0.860303 Evaluation's auc: 0.833779 [887] Train's auc: 0.860318 Evaluation's auc: 0.833773 [888] Train's auc: 0.860336 Evaluation's auc: 0.833768 [889] Train's auc: 0.860369 Evaluation's auc: 0.833787 [890] Train's auc: 0.860386 Evaluation's auc: 0.833799 [891] Train's auc: 0.860402 Evaluation's auc: 0.833801 [892] Train's auc: 0.860415 Evaluation's auc: 0.833794 [893] Train's auc: 0.860435 Evaluation's auc: 0.833803 [894] Train's auc: 0.860461 Evaluation's auc: 0.833814 [895] Train's auc: 0.860492 Evaluation's auc: 0.833824 [896] Train's auc: 0.860515 Evaluation's auc: 0.833843 [897] Train's auc: 0.860533 Evaluation's auc: 0.833859 [898] Train's auc: 0.860555 Evaluation's auc: 0.833857 [899] Train's auc: 0.860573 Evaluation's auc: 0.833865 [900] Train's auc: 0.860586 Evaluation's auc: 0.833864 [901] Train's auc: 0.8606 Evaluation's auc: 0.833861 [902] Train's auc: 0.860626 Evaluation's auc: 0.833873 [903] Train's auc: 0.860646 Evaluation's auc: 0.833889 [904] Train's auc: 0.860664 Evaluation's auc: 0.833883 [905] Train's auc: 0.860682 Evaluation's auc: 0.833893 [906] Train's auc: 0.860703 Evaluation's auc: 0.833921 [907] Train's auc: 0.860727 Evaluation's auc: 0.833938 [908] Train's auc: 0.860741 Evaluation's auc: 0.833933 [909] Train's auc: 0.86076 Evaluation's auc: 0.833929 [910] Train's auc: 0.860773 Evaluation's auc: 0.833927 [911] Train's auc: 0.860803 Evaluation's auc: 0.833948 [912] Train's auc: 0.86083 Evaluation's auc: 0.833958 [913] Train's auc: 0.860849 Evaluation's auc: 0.833969 [914] Train's auc: 0.860858 Evaluation's auc: 0.833963 [915] Train's auc: 0.860878 Evaluation's auc: 0.833957 [916] Train's auc: 0.8609 Evaluation's auc: 0.833958 [917] Train's auc: 0.860919 Evaluation's auc: 0.833983 [918] Train's auc: 0.86094 Evaluation's auc: 0.833988 [919] Train's auc: 0.86097 Evaluation's auc: 0.833995 [920] Train's auc: 0.860986 Evaluation's auc: 0.83401 [921] Train's auc: 0.861 Evaluation's auc: 0.834017 [922] Train's auc: 0.861025 Evaluation's auc: 0.834025 [923] Train's auc: 0.861046 Evaluation's auc: 0.834033 [924] Train's auc: 0.861068 Evaluation's auc: 0.834043 [925] Train's auc: 0.861094 Evaluation's auc: 0.834051 [926] Train's auc: 0.861111 Evaluation's auc: 0.834049 [927] Train's auc: 0.861133 Evaluation's auc: 0.834055 [928] Train's auc: 0.861149 Evaluation's auc: 0.834048 [929] Train's auc: 0.861173 Evaluation's auc: 0.834043 [930] Train's auc: 0.861193 Evaluation's auc: 0.834059 [931] Train's auc: 0.86122 Evaluation's auc: 0.834087 [932] Train's auc: 0.86124 Evaluation's auc: 0.834107 [933] Train's auc: 0.86126 Evaluation's auc: 0.83412 [934] Train's auc: 0.861284 Evaluation's auc: 0.834133 [935] Train's auc: 0.861298 Evaluation's auc: 0.834128 [936] Train's auc: 0.861314 Evaluation's auc: 0.834119 [937] Train's auc: 0.861337 Evaluation's auc: 0.834127 [938] Train's auc: 0.861357 Evaluation's auc: 0.834147 [939] Train's auc: 0.861375 Evaluation's auc: 0.834156 [940] Train's auc: 0.861402 Evaluation's auc: 0.834172 [941] Train's auc: 0.861415 Evaluation's auc: 0.834168 [942] Train's auc: 0.861437 Evaluation's auc: 0.834171 [943] Train's auc: 0.861456 Evaluation's auc: 0.834169 [944] Train's auc: 0.861485 Evaluation's auc: 0.834173 [945] Train's auc: 0.861509 Evaluation's auc: 0.834178 [946] Train's auc: 0.861528 Evaluation's auc: 0.834177 [947] Train's auc: 0.861543 Evaluation's auc: 0.834183 [948] Train's auc: 0.861555 Evaluation's auc: 0.834188 [949] Train's auc: 0.861573 Evaluation's auc: 0.834197 [950] Train's auc: 0.861582 Evaluation's auc: 0.834199 [951] Train's auc: 0.861606 Evaluation's auc: 0.83422 [952] Train's auc: 0.861626 Evaluation's auc: 0.834215 [953] Train's auc: 0.861639 Evaluation's auc: 0.83423 [954] Train's auc: 0.861656 Evaluation's auc: 0.834228 [955] Train's auc: 0.861677 Evaluation's auc: 0.834235 [956] Train's auc: 0.861704 Evaluation's auc: 0.834252 [957] Train's auc: 0.861725 Evaluation's auc: 0.834251 [958] Train's auc: 0.861744 Evaluation's auc: 0.834244 [959] Train's auc: 0.861776 Evaluation's auc: 0.834237 [960] Train's auc: 0.861798 Evaluation's auc: 0.834246 [961] Train's auc: 0.861815 Evaluation's auc: 0.834243 [962] Train's auc: 0.861837 Evaluation's auc: 0.834249 [963] Train's auc: 0.861854 Evaluation's auc: 0.834259 [964] Train's auc: 0.86187 Evaluation's auc: 0.834265 [965] Train's auc: 0.86188 Evaluation's auc: 0.834264 [966] Train's auc: 0.861898 Evaluation's auc: 0.834262 [967] Train's auc: 0.861914 Evaluation's auc: 0.834274 [968] Train's auc: 0.861944 Evaluation's auc: 0.83427 [969] Train's auc: 0.86196 Evaluation's auc: 0.834262 [970] Train's auc: 0.861975 Evaluation's auc: 0.83426 [971] Train's auc: 0.861997 Evaluation's auc: 0.834273 [972] Train's auc: 0.86202 Evaluation's auc: 0.834282 [973] Train's auc: 0.862036 Evaluation's auc: 0.834276 [974] Train's auc: 0.862053 Evaluation's auc: 0.834287 [975] Train's auc: 0.862077 Evaluation's auc: 0.834302 [976] Train's auc: 0.862086 Evaluation's auc: 0.834297 [977] Train's auc: 0.862111 Evaluation's auc: 0.83431 [978] Train's auc: 0.862134 Evaluation's auc: 0.834311 [979] Train's auc: 0.862158 Evaluation's auc: 0.834314 [980] Train's auc: 0.862171 Evaluation's auc: 0.834324 [981] Train's auc: 0.862191 Evaluation's auc: 0.83432 [982] Train's auc: 0.86222 Evaluation's auc: 0.834332 [983] Train's auc: 0.862245 Evaluation's auc: 0.834332 [984] Train's auc: 0.862267 Evaluation's auc: 0.834346 [985] Train's auc: 0.86228 Evaluation's auc: 0.83434 [986] Train's auc: 0.862303 Evaluation's auc: 0.834347 [987] Train's auc: 0.862321 Evaluation's auc: 0.834352 [988] Train's auc: 0.862337 Evaluation's auc: 0.834356 [989] Train's auc: 0.862356 Evaluation's auc: 0.834367 [990] Train's auc: 0.862371 Evaluation's auc: 0.83437 [991] Train's auc: 0.862389 Evaluation's auc: 0.834387 [992] Train's auc: 0.862396 Evaluation's auc: 0.834373 [993] Train's auc: 0.862409 Evaluation's auc: 0.834363 [994] Train's auc: 0.862434 Evaluation's auc: 0.834371 [995] Train's auc: 0.862457 Evaluation's auc: 0.834385 [996] Train's auc: 0.862479 Evaluation's auc: 0.834398 [997] Train's auc: 0.862501 Evaluation's auc: 0.834404 [998] Train's auc: 0.862515 Evaluation's auc: 0.834419 [999] Train's auc: 0.862537 Evaluation's auc: 0.834421 [1000] Train's auc: 0.862561 Evaluation's auc: 0.834431 [1001] Train's auc: 0.862571 Evaluation's auc: 0.834431 [1002] Train's auc: 0.862594 Evaluation's auc: 0.834436 [1003] Train's auc: 0.862611 Evaluation's auc: 0.834434 [1004] Train's auc: 0.862627 Evaluation's auc: 0.83444 [1005] Train's auc: 0.862648 Evaluation's auc: 0.834461 [1006] Train's auc: 0.862673 Evaluation's auc: 0.834472 [1007] Train's auc: 0.862695 Evaluation's auc: 0.834474 [1008] Train's auc: 0.862719 Evaluation's auc: 0.834476 [1009] Train's auc: 0.862744 Evaluation's auc: 0.834495 [1010] Train's auc: 0.862761 Evaluation's auc: 0.8345 [1011] Train's auc: 0.862783 Evaluation's auc: 0.83451 [1012] Train's auc: 0.862796 Evaluation's auc: 0.834513 [1013] Train's auc: 0.862806 Evaluation's auc: 0.834509 [1014] Train's auc: 0.862823 Evaluation's auc: 0.83452 [1015] Train's auc: 0.86285 Evaluation's auc: 0.834523 [1016] Train's auc: 0.862865 Evaluation's auc: 0.834536 [1017] Train's auc: 0.86289 Evaluation's auc: 0.834544 [1018] Train's auc: 0.862903 Evaluation's auc: 0.834542 [1019] Train's auc: 0.862919 Evaluation's auc: 0.834549 [1020] Train's auc: 0.862932 Evaluation's auc: 0.834563 [1021] Train's auc: 0.862951 Evaluation's auc: 0.834552 [1022] Train's auc: 0.862966 Evaluation's auc: 0.834548 [1023] Train's auc: 0.862985 Evaluation's auc: 0.834553 [1024] Train's auc: 0.863009 Evaluation's auc: 0.834563 [1025] Train's auc: 0.863019 Evaluation's auc: 0.834555 [1026] Train's auc: 0.863039 Evaluation's auc: 0.83455 [1027] Train's auc: 0.863058 Evaluation's auc: 0.834553 [1028] Train's auc: 0.863084 Evaluation's auc: 0.834571 [1029] Train's auc: 0.863105 Evaluation's auc: 0.83457 [1030] Train's auc: 0.863131 Evaluation's auc: 0.834581 [1031] Train's auc: 0.863149 Evaluation's auc: 0.834577 [1032] Train's auc: 0.863165 Evaluation's auc: 0.834597 [1033] Train's auc: 0.863187 Evaluation's auc: 0.834609 [1034] Train's auc: 0.863197 Evaluation's auc: 0.834613 [1035] Train's auc: 0.863215 Evaluation's auc: 0.834614 [1036] Train's auc: 0.86324 Evaluation's auc: 0.834621 [1037] Train's auc: 0.863261 Evaluation's auc: 0.834628 [1038] Train's auc: 0.863286 Evaluation's auc: 0.834628 [1039] Train's auc: 0.863294 Evaluation's auc: 0.834621 [1040] Train's auc: 0.863308 Evaluation's auc: 0.834626 [1041] Train's auc: 0.863324 Evaluation's auc: 0.83462 [1042] Train's auc: 0.863335 Evaluation's auc: 0.83463 [1043] Train's auc: 0.863356 Evaluation's auc: 0.834635 [1044] Train's auc: 0.86337 Evaluation's auc: 0.834632 [1045] Train's auc: 0.863386 Evaluation's auc: 0.834635 [1046] Train's auc: 0.863404 Evaluation's auc: 0.834656 [1047] Train's auc: 0.86342 Evaluation's auc: 0.834652 [1048] Train's auc: 0.863431 Evaluation's auc: 0.834657 [1049] Train's auc: 0.863452 Evaluation's auc: 0.834668 [1050] Train's auc: 0.863472 Evaluation's auc: 0.834672 [1051] Train's auc: 0.863493 Evaluation's auc: 0.83467 [1052] Train's auc: 0.86352 Evaluation's auc: 0.834693 [1053] Train's auc: 0.863538 Evaluation's auc: 0.834691 [1054] Train's auc: 0.863556 Evaluation's auc: 0.83471 [1055] Train's auc: 0.863571 Evaluation's auc: 0.834696 [1056] Train's auc: 0.863596 Evaluation's auc: 0.834717 [1057] Train's auc: 0.863608 Evaluation's auc: 0.834711 [1058] Train's auc: 0.863636 Evaluation's auc: 0.834712 [1059] Train's auc: 0.863657 Evaluation's auc: 0.834722 [1060] Train's auc: 0.863668 Evaluation's auc: 0.834729 [1061] Train's auc: 0.863683 Evaluation's auc: 0.834733 [1062] Train's auc: 0.863697 Evaluation's auc: 0.834743 [1063] Train's auc: 0.863704 Evaluation's auc: 0.834758 [1064] Train's auc: 0.863718 Evaluation's auc: 0.834749 [1065] Train's auc: 0.863737 Evaluation's auc: 0.834756 [1066] Train's auc: 0.863758 Evaluation's auc: 0.834788 [1067] Train's auc: 0.863779 Evaluation's auc: 0.834788 [1068] Train's auc: 0.863796 Evaluation's auc: 0.834808 [1069] Train's auc: 0.863807 Evaluation's auc: 0.834816 [1070] Train's auc: 0.86383 Evaluation's auc: 0.834826 [1071] Train's auc: 0.863848 Evaluation's auc: 0.834835 [1072] Train's auc: 0.863864 Evaluation's auc: 0.834844 [1073] Train's auc: 0.863887 Evaluation's auc: 0.834859 [1074] Train's auc: 0.863904 Evaluation's auc: 0.83487 [1075] Train's auc: 0.863922 Evaluation's auc: 0.834882 [1076] Train's auc: 0.863939 Evaluation's auc: 0.83489 [1077] Train's auc: 0.863953 Evaluation's auc: 0.834906 [1078] Train's auc: 0.863971 Evaluation's auc: 0.834925 [1079] Train's auc: 0.863988 Evaluation's auc: 0.834922 [1080] Train's auc: 0.864002 Evaluation's auc: 0.83492 [1081] Train's auc: 0.864023 Evaluation's auc: 0.834922 [1082] Train's auc: 0.864043 Evaluation's auc: 0.834938 [1083] Train's auc: 0.864056 Evaluation's auc: 0.834931 [1084] Train's auc: 0.864069 Evaluation's auc: 0.834928 [1085] Train's auc: 0.864076 Evaluation's auc: 0.834925 [1086] Train's auc: 0.864098 Evaluation's auc: 0.834922 [1087] Train's auc: 0.864113 Evaluation's auc: 0.834921 [1088] Train's auc: 0.86413 Evaluation's auc: 0.834927 [1089] Train's auc: 0.864148 Evaluation's auc: 0.834924 [1090] Train's auc: 0.864171 Evaluation's auc: 0.834924 [1091] Train's auc: 0.864193 Evaluation's auc: 0.834931 [1092] Train's auc: 0.864216 Evaluation's auc: 0.834946 [1093] Train's auc: 0.864236 Evaluation's auc: 0.83495 [1094] Train's auc: 0.864265 Evaluation's auc: 0.834965 [1095] Train's auc: 0.864286 Evaluation's auc: 0.834975 [1096] Train's auc: 0.864305 Evaluation's auc: 0.834982 [1097] Train's auc: 0.864317 Evaluation's auc: 0.834979 [1098] Train's auc: 0.864339 Evaluation's auc: 0.834985 [1099] Train's auc: 0.864358 Evaluation's auc: 0.835004 [1100] Train's auc: 0.864378 Evaluation's auc: 0.835016 [1101] Train's auc: 0.864399 Evaluation's auc: 0.835033 [1102] Train's auc: 0.864425 Evaluation's auc: 0.835039 [1103] Train's auc: 0.864436 Evaluation's auc: 0.835042 [1104] Train's auc: 0.864453 Evaluation's auc: 0.83504 [1105] Train's auc: 0.864467 Evaluation's auc: 0.835036 [1106] Train's auc: 0.86448 Evaluation's auc: 0.835047 [1107] Train's auc: 0.864497 Evaluation's auc: 0.835048 [1108] Train's auc: 0.864523 Evaluation's auc: 0.835053 [1109] Train's auc: 0.864548 Evaluation's auc: 0.83507 [1110] Train's auc: 0.864564 Evaluation's auc: 0.835074 [1111] Train's auc: 0.864582 Evaluation's auc: 0.835084 [1112] Train's auc: 0.864599 Evaluation's auc: 0.835088 [1113] Train's auc: 0.864617 Evaluation's auc: 0.835093 [1114] Train's auc: 0.864635 Evaluation's auc: 0.835091 [1115] Train's auc: 0.86466 Evaluation's auc: 0.835092 [1116] Train's auc: 0.864668 Evaluation's auc: 0.835093 [1117] Train's auc: 0.864687 Evaluation's auc: 0.835106 [1118] Train's auc: 0.864696 Evaluation's auc: 0.835102 [1119] Train's auc: 0.864719 Evaluation's auc: 0.835117 [1120] Train's auc: 0.864738 Evaluation's auc: 0.83514 [1121] Train's auc: 0.864757 Evaluation's auc: 0.835164 [1122] Train's auc: 0.864774 Evaluation's auc: 0.835163 [1123] Train's auc: 0.864788 Evaluation's auc: 0.835173 [1124] Train's auc: 0.864816 Evaluation's auc: 0.835181 [1125] Train's auc: 0.86483 Evaluation's auc: 0.835177 [1126] Train's auc: 0.864843 Evaluation's auc: 0.835174 [1127] Train's auc: 0.864865 Evaluation's auc: 0.835173 [1128] Train's auc: 0.86487 Evaluation's auc: 0.835166 [1129] Train's auc: 0.864891 Evaluation's auc: 0.835172 [1130] Train's auc: 0.864908 Evaluation's auc: 0.835167 [1131] Train's auc: 0.864924 Evaluation's auc: 0.835177 [1132] Train's auc: 0.864938 Evaluation's auc: 0.835177 [1133] Train's auc: 0.864958 Evaluation's auc: 0.83519 [1134] Train's auc: 0.864974 Evaluation's auc: 0.835198 [1135] Train's auc: 0.864991 Evaluation's auc: 0.835208 [1136] Train's auc: 0.865005 Evaluation's auc: 0.835214 [1137] Train's auc: 0.865019 Evaluation's auc: 0.83522 [1138] Train's auc: 0.865041 Evaluation's auc: 0.835221 [1139] Train's auc: 0.865056 Evaluation's auc: 0.835234 [1140] Train's auc: 0.865071 Evaluation's auc: 0.835233 [1141] Train's auc: 0.865091 Evaluation's auc: 0.83525 [1142] Train's auc: 0.865105 Evaluation's auc: 0.835255 [1143] Train's auc: 0.865119 Evaluation's auc: 0.835252 [1144] Train's auc: 0.865135 Evaluation's auc: 0.835257 [1145] Train's auc: 0.865157 Evaluation's auc: 0.835261 [1146] Train's auc: 0.865169 Evaluation's auc: 0.835266 [1147] Train's auc: 0.86519 Evaluation's auc: 0.835276 [1148] Train's auc: 0.865206 Evaluation's auc: 0.835284 [1149] Train's auc: 0.865232 Evaluation's auc: 0.835289 [1150] Train's auc: 0.865243 Evaluation's auc: 0.835294 [1151] Train's auc: 0.86526 Evaluation's auc: 0.835308 [1152] Train's auc: 0.865283 Evaluation's auc: 0.835309 [1153] Train's auc: 0.865306 Evaluation's auc: 0.835329 [1154] Train's auc: 0.865324 Evaluation's auc: 0.835334 [1155] Train's auc: 0.865332 Evaluation's auc: 0.835328 [1156] Train's auc: 0.865349 Evaluation's auc: 0.835334 [1157] Train's auc: 0.865368 Evaluation's auc: 0.835355 [1158] Train's auc: 0.865383 Evaluation's auc: 0.835364 [1159] Train's auc: 0.865398 Evaluation's auc: 0.83536 [1160] Train's auc: 0.865413 Evaluation's auc: 0.835354 [1161] Train's auc: 0.865425 Evaluation's auc: 0.835366 [1162] Train's auc: 0.865441 Evaluation's auc: 0.835373 [1163] Train's auc: 0.865461 Evaluation's auc: 0.835377 [1164] Train's auc: 0.865485 Evaluation's auc: 0.835377 [1165] Train's auc: 0.865503 Evaluation's auc: 0.835391 [1166] Train's auc: 0.865524 Evaluation's auc: 0.835404 [1167] Train's auc: 0.865537 Evaluation's auc: 0.835392 [1168] Train's auc: 0.865568 Evaluation's auc: 0.8354 [1169] Train's auc: 0.865588 Evaluation's auc: 0.835413 [1170] Train's auc: 0.865604 Evaluation's auc: 0.835407 [1171] Train's auc: 0.865616 Evaluation's auc: 0.835403 [1172] Train's auc: 0.86563 Evaluation's auc: 0.835411 [1173] Train's auc: 0.865644 Evaluation's auc: 0.835412 [1174] Train's auc: 0.865663 Evaluation's auc: 0.835411 [1175] Train's auc: 0.865676 Evaluation's auc: 0.835412 [1176] Train's auc: 0.865687 Evaluation's auc: 0.835411 [1177] Train's auc: 0.865707 Evaluation's auc: 0.835415 [1178] Train's auc: 0.865721 Evaluation's auc: 0.83542 [1179] Train's auc: 0.865745 Evaluation's auc: 0.835427 [1180] Train's auc: 0.865767 Evaluation's auc: 0.835439 [1181] Train's auc: 0.865782 Evaluation's auc: 0.835445 [1182] Train's auc: 0.865792 Evaluation's auc: 0.835454 [1183] Train's auc: 0.865805 Evaluation's auc: 0.835453 [1184] Train's auc: 0.865826 Evaluation's auc: 0.835465 [1185] Train's auc: 0.865836 Evaluation's auc: 0.835459 [1186] Train's auc: 0.865854 Evaluation's auc: 0.835464 [1187] Train's auc: 0.865874 Evaluation's auc: 0.835459 [1188] Train's auc: 0.86588 Evaluation's auc: 0.835459 [1189] Train's auc: 0.865901 Evaluation's auc: 0.835462 [1190] Train's auc: 0.865917 Evaluation's auc: 0.835458 [1191] Train's auc: 0.865938 Evaluation's auc: 0.835453 [1192] Train's auc: 0.865949 Evaluation's auc: 0.83546 [1193] Train's auc: 0.86596 Evaluation's auc: 0.835464 [1194] Train's auc: 0.865982 Evaluation's auc: 0.835473 [1195] Train's auc: 0.866004 Evaluation's auc: 0.835476 [1196] Train's auc: 0.86602 Evaluation's auc: 0.835474 [1197] Train's auc: 0.866033 Evaluation's auc: 0.835465 [1198] Train's auc: 0.866053 Evaluation's auc: 0.835465 [1199] Train's auc: 0.866073 Evaluation's auc: 0.83547 [1200] Train's auc: 0.866085 Evaluation's auc: 0.835479 [1201] Train's auc: 0.866099 Evaluation's auc: 0.835479 [1202] Train's auc: 0.866115 Evaluation's auc: 0.835483 [1203] Train's auc: 0.866133 Evaluation's auc: 0.835486 [1204] Train's auc: 0.866145 Evaluation's auc: 0.83548 [1205] Train's auc: 0.866163 Evaluation's auc: 0.835486 [1206] Train's auc: 0.866184 Evaluation's auc: 0.835483 [1207] Train's auc: 0.866205 Evaluation's auc: 0.8355 [1208] Train's auc: 0.866217 Evaluation's auc: 0.835508 [1209] Train's auc: 0.86623 Evaluation's auc: 0.835516 [1210] Train's auc: 0.866251 Evaluation's auc: 0.83551 [1211] Train's auc: 0.866272 Evaluation's auc: 0.835527 [1212] Train's auc: 0.866286 Evaluation's auc: 0.835525 [1213] Train's auc: 0.866308 Evaluation's auc: 0.835522 [1214] Train's auc: 0.866321 Evaluation's auc: 0.835531 [1215] Train's auc: 0.866342 Evaluation's auc: 0.83553 [1216] Train's auc: 0.866363 Evaluation's auc: 0.835528 [1217] Train's auc: 0.866384 Evaluation's auc: 0.835537 [1218] Train's auc: 0.866396 Evaluation's auc: 0.835536 [1219] Train's auc: 0.866405 Evaluation's auc: 0.835536 [1220] Train's auc: 0.866421 Evaluation's auc: 0.83553 [1221] Train's auc: 0.866444 Evaluation's auc: 0.835535 [1222] Train's auc: 0.866465 Evaluation's auc: 0.835551 [1223] Train's auc: 0.866482 Evaluation's auc: 0.835549 [1224] Train's auc: 0.866492 Evaluation's auc: 0.835552 [1225] Train's auc: 0.866508 Evaluation's auc: 0.835554 [1226] Train's auc: 0.866526 Evaluation's auc: 0.835562 [1227] Train's auc: 0.866545 Evaluation's auc: 0.835556 [1228] Train's auc: 0.866564 Evaluation's auc: 0.835557 [1229] Train's auc: 0.866579 Evaluation's auc: 0.835556 [1230] Train's auc: 0.866596 Evaluation's auc: 0.835564 [1231] Train's auc: 0.866614 Evaluation's auc: 0.835572 [1232] Train's auc: 0.866632 Evaluation's auc: 0.835571 [1233] Train's auc: 0.866645 Evaluation's auc: 0.835571 [1234] Train's auc: 0.866658 Evaluation's auc: 0.835565 [1235] Train's auc: 0.866678 Evaluation's auc: 0.835574 [1236] Train's auc: 0.866694 Evaluation's auc: 0.835585 [1237] Train's auc: 0.866713 Evaluation's auc: 0.835588 [1238] Train's auc: 0.866724 Evaluation's auc: 0.835603 [1239] Train's auc: 0.866733 Evaluation's auc: 0.835601 [1240] Train's auc: 0.866755 Evaluation's auc: 0.835595 [1241] Train's auc: 0.866772 Evaluation's auc: 0.835591 [1242] Train's auc: 0.866788 Evaluation's auc: 0.835588 [1243] Train's auc: 0.866804 Evaluation's auc: 0.835593 [1244] Train's auc: 0.866819 Evaluation's auc: 0.835593 [1245] Train's auc: 0.866836 Evaluation's auc: 0.835593 [1246] Train's auc: 0.866853 Evaluation's auc: 0.835591 [1247] Train's auc: 0.866861 Evaluation's auc: 0.835593 [1248] Train's auc: 0.866877 Evaluation's auc: 0.835601 [1249] Train's auc: 0.866891 Evaluation's auc: 0.835605 [1250] Train's auc: 0.866902 Evaluation's auc: 0.835606 [1251] Train's auc: 0.866921 Evaluation's auc: 0.835612 [1252] Train's auc: 0.866944 Evaluation's auc: 0.835622 [1253] Train's auc: 0.866959 Evaluation's auc: 0.835633 [1254] Train's auc: 0.866978 Evaluation's auc: 0.835642 [1255] Train's auc: 0.866995 Evaluation's auc: 0.835649 [1256] Train's auc: 0.867011 Evaluation's auc: 0.835658 [1257] Train's auc: 0.867026 Evaluation's auc: 0.835659 [1258] Train's auc: 0.867046 Evaluation's auc: 0.835666 [1259] Train's auc: 0.867056 Evaluation's auc: 0.835655 [1260] Train's auc: 0.867075 Evaluation's auc: 0.835663 [1261] Train's auc: 0.867085 Evaluation's auc: 0.835658 [1262] Train's auc: 0.867104 Evaluation's auc: 0.835662 [1263] Train's auc: 0.867119 Evaluation's auc: 0.835668 [1264] Train's auc: 0.867132 Evaluation's auc: 0.83568 [1265] Train's auc: 0.867152 Evaluation's auc: 0.835675 [1266] Train's auc: 0.867165 Evaluation's auc: 0.835676 [1267] Train's auc: 0.867186 Evaluation's auc: 0.835678 [1268] Train's auc: 0.867199 Evaluation's auc: 0.835686 [1269] Train's auc: 0.867207 Evaluation's auc: 0.835686 [1270] Train's auc: 0.867227 Evaluation's auc: 0.835694 [1271] Train's auc: 0.867248 Evaluation's auc: 0.835704 [1272] Train's auc: 0.86726 Evaluation's auc: 0.835708 [1273] Train's auc: 0.867278 Evaluation's auc: 0.835709 [1274] Train's auc: 0.867288 Evaluation's auc: 0.835705 [1275] Train's auc: 0.867303 Evaluation's auc: 0.835705 [1276] Train's auc: 0.867322 Evaluation's auc: 0.835712 [1277] Train's auc: 0.867342 Evaluation's auc: 0.835717 [1278] Train's auc: 0.867355 Evaluation's auc: 0.835725 [1279] Train's auc: 0.86737 Evaluation's auc: 0.835725 [1280] Train's auc: 0.867389 Evaluation's auc: 0.835733 [1281] Train's auc: 0.867402 Evaluation's auc: 0.835733 [1282] Train's auc: 0.867427 Evaluation's auc: 0.835751 [1283] Train's auc: 0.867445 Evaluation's auc: 0.835756 [1284] Train's auc: 0.86746 Evaluation's auc: 0.835772 [1285] Train's auc: 0.867474 Evaluation's auc: 0.835771 [1286] Train's auc: 0.86749 Evaluation's auc: 0.835771 [1287] Train's auc: 0.867509 Evaluation's auc: 0.835771 [1288] Train's auc: 0.867528 Evaluation's auc: 0.835775 [1289] Train's auc: 0.867545 Evaluation's auc: 0.835793 [1290] Train's auc: 0.867559 Evaluation's auc: 0.835796 [1291] Train's auc: 0.867576 Evaluation's auc: 0.835795 [1292] Train's auc: 0.867586 Evaluation's auc: 0.835802 [1293] Train's auc: 0.867609 Evaluation's auc: 0.835804 [1294] Train's auc: 0.867617 Evaluation's auc: 0.835802 [1295] Train's auc: 0.867635 Evaluation's auc: 0.835816 [1296] Train's auc: 0.867655 Evaluation's auc: 0.835839 [1297] Train's auc: 0.867677 Evaluation's auc: 0.835843 [1298] Train's auc: 0.867694 Evaluation's auc: 0.835857 [1299] Train's auc: 0.867711 Evaluation's auc: 0.835861 [1300] Train's auc: 0.867732 Evaluation's auc: 0.835862 [1301] Train's auc: 0.867742 Evaluation's auc: 0.835864 [1302] Train's auc: 0.867764 Evaluation's auc: 0.835865 [1303] Train's auc: 0.867777 Evaluation's auc: 0.835867 [1304] Train's auc: 0.867791 Evaluation's auc: 0.835867 [1305] Train's auc: 0.867805 Evaluation's auc: 0.83587 [1306] Train's auc: 0.867814 Evaluation's auc: 0.835862 [1307] Train's auc: 0.867836 Evaluation's auc: 0.835867 [1308] Train's auc: 0.867859 Evaluation's auc: 0.835874 [1309] Train's auc: 0.867878 Evaluation's auc: 0.835878 [1310] Train's auc: 0.867897 Evaluation's auc: 0.835883 [1311] Train's auc: 0.867916 Evaluation's auc: 0.835892 [1312] Train's auc: 0.867933 Evaluation's auc: 0.835894 [1313] Train's auc: 0.867943 Evaluation's auc: 0.835896 [1314] Train's auc: 0.867962 Evaluation's auc: 0.835902 [1315] Train's auc: 0.867981 Evaluation's auc: 0.835906 [1316] Train's auc: 0.867999 Evaluation's auc: 0.835911 [1317] Train's auc: 0.868017 Evaluation's auc: 0.835909 [1318] Train's auc: 0.868031 Evaluation's auc: 0.835911 [1319] Train's auc: 0.868054 Evaluation's auc: 0.835919 [1320] Train's auc: 0.868076 Evaluation's auc: 0.835909 [1321] Train's auc: 0.868089 Evaluation's auc: 0.835922 [1322] Train's auc: 0.86811 Evaluation's auc: 0.835922 [1323] Train's auc: 0.868127 Evaluation's auc: 0.835936 [1324] Train's auc: 0.868145 Evaluation's auc: 0.835934 [1325] Train's auc: 0.86816 Evaluation's auc: 0.835934 [1326] Train's auc: 0.868183 Evaluation's auc: 0.835935 [1327] Train's auc: 0.868195 Evaluation's auc: 0.835937 [1328] Train's auc: 0.868212 Evaluation's auc: 0.835921 [1329] Train's auc: 0.868223 Evaluation's auc: 0.835918 [1330] Train's auc: 0.868237 Evaluation's auc: 0.835908 [1331] Train's auc: 0.868245 Evaluation's auc: 0.835904 [1332] Train's auc: 0.868258 Evaluation's auc: 0.835895 [1333] Train's auc: 0.868278 Evaluation's auc: 0.835909 [1334] Train's auc: 0.868293 Evaluation's auc: 0.835925 [1335] Train's auc: 0.86831 Evaluation's auc: 0.835945 [1336] Train's auc: 0.868332 Evaluation's auc: 0.835965 [1337] Train's auc: 0.86835 Evaluation's auc: 0.835976 [1338] Train's auc: 0.868365 Evaluation's auc: 0.835992 [1339] Train's auc: 0.868375 Evaluation's auc: 0.835989 [1340] Train's auc: 0.868392 Evaluation's auc: 0.83599 [1341] Train's auc: 0.86841 Evaluation's auc: 0.836004 [1342] Train's auc: 0.868419 Evaluation's auc: 0.836015 [1343] Train's auc: 0.868432 Evaluation's auc: 0.836019 [1344] Train's auc: 0.868446 Evaluation's auc: 0.836021 [1345] Train's auc: 0.868466 Evaluation's auc: 0.836032 [1346] Train's auc: 0.868484 Evaluation's auc: 0.836036 [1347] Train's auc: 0.868495 Evaluation's auc: 0.836035 [1348] Train's auc: 0.86851 Evaluation's auc: 0.836039 [1349] Train's auc: 0.868533 Evaluation's auc: 0.836063 [1350] Train's auc: 0.868546 Evaluation's auc: 0.836075 [1351] Train's auc: 0.868562 Evaluation's auc: 0.836082 [1352] Train's auc: 0.868574 Evaluation's auc: 0.836084 [1353] Train's auc: 0.868593 Evaluation's auc: 0.836101 [1354] Train's auc: 0.868603 Evaluation's auc: 0.836107 [1355] Train's auc: 0.868618 Evaluation's auc: 0.83611 [1356] Train's auc: 0.868638 Evaluation's auc: 0.836123 [1357] Train's auc: 0.868654 Evaluation's auc: 0.836118 [1358] Train's auc: 0.868672 Evaluation's auc: 0.836122 [1359] Train's auc: 0.868686 Evaluation's auc: 0.836118 [1360] Train's auc: 0.868708 Evaluation's auc: 0.836137 [1361] Train's auc: 0.868712 Evaluation's auc: 0.836133 [1362] Train's auc: 0.86873 Evaluation's auc: 0.836143 [1363] Train's auc: 0.868748 Evaluation's auc: 0.836148 [1364] Train's auc: 0.868761 Evaluation's auc: 0.836146 [1365] Train's auc: 0.868774 Evaluation's auc: 0.836158 [1366] Train's auc: 0.868794 Evaluation's auc: 0.836152 [1367] Train's auc: 0.86881 Evaluation's auc: 0.836155 [1368] Train's auc: 0.868823 Evaluation's auc: 0.836175 [1369] Train's auc: 0.868826 Evaluation's auc: 0.836169 [1370] Train's auc: 0.868845 Evaluation's auc: 0.836176 [1371] Train's auc: 0.868858 Evaluation's auc: 0.836191 [1372] Train's auc: 0.868877 Evaluation's auc: 0.836197 [1373] Train's auc: 0.86889 Evaluation's auc: 0.836201 [1374] Train's auc: 0.86891 Evaluation's auc: 0.836207 [1375] Train's auc: 0.868923 Evaluation's auc: 0.836199 [1376] Train's auc: 0.868943 Evaluation's auc: 0.836191 [1377] Train's auc: 0.868958 Evaluation's auc: 0.836198 [1378] Train's auc: 0.868969 Evaluation's auc: 0.836199 [1379] Train's auc: 0.868986 Evaluation's auc: 0.836206 [1380] Train's auc: 0.868994 Evaluation's auc: 0.836208 [1381] Train's auc: 0.86901 Evaluation's auc: 0.836212 [1382] Train's auc: 0.869021 Evaluation's auc: 0.836206 [1383] Train's auc: 0.869039 Evaluation's auc: 0.836224 [1384] Train's auc: 0.869054 Evaluation's auc: 0.836234 [1385] Train's auc: 0.869065 Evaluation's auc: 0.836238 [1386] Train's auc: 0.869073 Evaluation's auc: 0.836241 [1387] Train's auc: 0.869085 Evaluation's auc: 0.836249 [1388] Train's auc: 0.869095 Evaluation's auc: 0.836237 [1389] Train's auc: 0.869115 Evaluation's auc: 0.836243 [1390] Train's auc: 0.869129 Evaluation's auc: 0.836257 [1391] Train's auc: 0.869149 Evaluation's auc: 0.836277 [1392] Train's auc: 0.869164 Evaluation's auc: 0.836268 [1393] Train's auc: 0.869181 Evaluation's auc: 0.836271 [1394] Train's auc: 0.8692 Evaluation's auc: 0.836292 [1395] Train's auc: 0.869216 Evaluation's auc: 0.836308 [1396] Train's auc: 0.869231 Evaluation's auc: 0.836315 [1397] Train's auc: 0.869247 Evaluation's auc: 0.836322 [1398] Train's auc: 0.869261 Evaluation's auc: 0.836332 [1399] Train's auc: 0.869276 Evaluation's auc: 0.836322 [1400] Train's auc: 0.869288 Evaluation's auc: 0.836321 [1401] Train's auc: 0.869304 Evaluation's auc: 0.83632 [1402] Train's auc: 0.869321 Evaluation's auc: 0.836335 [1403] Train's auc: 0.869338 Evaluation's auc: 0.836356 [1404] Train's auc: 0.869354 Evaluation's auc: 0.836354 [1405] Train's auc: 0.86937 Evaluation's auc: 0.836355 [1406] Train's auc: 0.869385 Evaluation's auc: 0.836361 [1407] Train's auc: 0.869398 Evaluation's auc: 0.836363 [1408] Train's auc: 0.869417 Evaluation's auc: 0.836358 [1409] Train's auc: 0.869435 Evaluation's auc: 0.836365 [1410] Train's auc: 0.869457 Evaluation's auc: 0.836374 [1411] Train's auc: 0.86947 Evaluation's auc: 0.836366 [1412] Train's auc: 0.869484 Evaluation's auc: 0.836372 [1413] Train's auc: 0.869499 Evaluation's auc: 0.836389 [1414] Train's auc: 0.86951 Evaluation's auc: 0.8364 [1415] Train's auc: 0.869531 Evaluation's auc: 0.836389 [1416] Train's auc: 0.869546 Evaluation's auc: 0.836398 [1417] Train's auc: 0.869562 Evaluation's auc: 0.836397 [1418] Train's auc: 0.869579 Evaluation's auc: 0.836408 [1419] Train's auc: 0.869597 Evaluation's auc: 0.836413 [1420] Train's auc: 0.869614 Evaluation's auc: 0.836424 [1421] Train's auc: 0.869631 Evaluation's auc: 0.836445 [1422] Train's auc: 0.869645 Evaluation's auc: 0.836456 [1423] Train's auc: 0.869659 Evaluation's auc: 0.836466 [1424] Train's auc: 0.86967 Evaluation's auc: 0.836467 [1425] Train's auc: 0.869687 Evaluation's auc: 0.836487 [1426] Train's auc: 0.8697 Evaluation's auc: 0.836499 [1427] Train's auc: 0.86971 Evaluation's auc: 0.836497 [1428] Train's auc: 0.869724 Evaluation's auc: 0.836506 [1429] Train's auc: 0.86974 Evaluation's auc: 0.83651 [1430] Train's auc: 0.869756 Evaluation's auc: 0.836503 [1431] Train's auc: 0.869765 Evaluation's auc: 0.836503 [1432] Train's auc: 0.869782 Evaluation's auc: 0.836507 [1433] Train's auc: 0.869796 Evaluation's auc: 0.836502 [1434] Train's auc: 0.869815 Evaluation's auc: 0.836509 [1435] Train's auc: 0.869828 Evaluation's auc: 0.836516 [1436] Train's auc: 0.869838 Evaluation's auc: 0.836518 [1437] Train's auc: 0.869854 Evaluation's auc: 0.836534 [1438] Train's auc: 0.869865 Evaluation's auc: 0.836532 [1439] Train's auc: 0.869881 Evaluation's auc: 0.836541 [1440] Train's auc: 0.869891 Evaluation's auc: 0.836532 [1441] Train's auc: 0.8699 Evaluation's auc: 0.836535 [1442] Train's auc: 0.869917 Evaluation's auc: 0.836551 [1443] Train's auc: 0.869931 Evaluation's auc: 0.836562 [1444] Train's auc: 0.869947 Evaluation's auc: 0.836553 [1445] Train's auc: 0.869961 Evaluation's auc: 0.836561 [1446] Train's auc: 0.869973 Evaluation's auc: 0.836564 [1447] Train's auc: 0.869986 Evaluation's auc: 0.836563 [1448] Train's auc: 0.870001 Evaluation's auc: 0.836571 [1449] Train's auc: 0.870012 Evaluation's auc: 0.836574 [1450] Train's auc: 0.870029 Evaluation's auc: 0.836595 [1451] Train's auc: 0.87004 Evaluation's auc: 0.836593 [1452] Train's auc: 0.870055 Evaluation's auc: 0.836605 [1453] Train's auc: 0.870068 Evaluation's auc: 0.83661 [1454] Train's auc: 0.870084 Evaluation's auc: 0.836615 [1455] Train's auc: 0.870098 Evaluation's auc: 0.836624 [1456] Train's auc: 0.870107 Evaluation's auc: 0.836624 [1457] Train's auc: 0.870127 Evaluation's auc: 0.836637 [1458] Train's auc: 0.870139 Evaluation's auc: 0.836637 [1459] Train's auc: 0.870148 Evaluation's auc: 0.836629 [1460] Train's auc: 0.870167 Evaluation's auc: 0.83664 [1461] Train's auc: 0.870181 Evaluation's auc: 0.836645 [1462] Train's auc: 0.870192 Evaluation's auc: 0.836652 [1463] Train's auc: 0.870208 Evaluation's auc: 0.836666 [1464] Train's auc: 0.870221 Evaluation's auc: 0.836669 [1465] Train's auc: 0.870233 Evaluation's auc: 0.836676 [1466] Train's auc: 0.870249 Evaluation's auc: 0.836679 [1467] Train's auc: 0.87026 Evaluation's auc: 0.836687 [1468] Train's auc: 0.870281 Evaluation's auc: 0.83669 [1469] Train's auc: 0.870293 Evaluation's auc: 0.836685 [1470] Train's auc: 0.870308 Evaluation's auc: 0.836685 [1471] Train's auc: 0.870321 Evaluation's auc: 0.836699 [1472] Train's auc: 0.870333 Evaluation's auc: 0.836705 [1473] Train's auc: 0.87034 Evaluation's auc: 0.836692 [1474] Train's auc: 0.870355 Evaluation's auc: 0.8367 [1475] Train's auc: 0.870371 Evaluation's auc: 0.836714 [1476] Train's auc: 0.870387 Evaluation's auc: 0.836734 [1477] Train's auc: 0.870406 Evaluation's auc: 0.836745 [1478] Train's auc: 0.870417 Evaluation's auc: 0.836753 [1479] Train's auc: 0.87043 Evaluation's auc: 0.836757 [1480] Train's auc: 0.870442 Evaluation's auc: 0.83678 [1481] Train's auc: 0.870454 Evaluation's auc: 0.836785 [1482] Train's auc: 0.870472 Evaluation's auc: 0.83678 [1483] Train's auc: 0.870482 Evaluation's auc: 0.836788 [1484] Train's auc: 0.870495 Evaluation's auc: 0.836786 [1485] Train's auc: 0.870509 Evaluation's auc: 0.836791 [1486] Train's auc: 0.870527 Evaluation's auc: 0.836817 [1487] Train's auc: 0.870533 Evaluation's auc: 0.836825 [1488] Train's auc: 0.87055 Evaluation's auc: 0.83685 [1489] Train's auc: 0.870566 Evaluation's auc: 0.836849 [1490] Train's auc: 0.870574 Evaluation's auc: 0.836858 [1491] Train's auc: 0.87059 Evaluation's auc: 0.836862 [1492] Train's auc: 0.870602 Evaluation's auc: 0.836877 [1493] Train's auc: 0.87062 Evaluation's auc: 0.836882 [1494] Train's auc: 0.870633 Evaluation's auc: 0.836888 [1495] Train's auc: 0.870644 Evaluation's auc: 0.836896 [1496] Train's auc: 0.870654 Evaluation's auc: 0.836903 [1497] Train's auc: 0.870668 Evaluation's auc: 0.836912 [1498] Train's auc: 0.870684 Evaluation's auc: 0.836916 [1499] Train's auc: 0.870699 Evaluation's auc: 0.836939 [1500] Train's auc: 0.87071 Evaluation's auc: 0.83695 [1501] Train's auc: 0.870727 Evaluation's auc: 0.836952 [1502] Train's auc: 0.870735 Evaluation's auc: 0.836955 [1503] Train's auc: 0.870752 Evaluation's auc: 0.836962 [1504] Train's auc: 0.870771 Evaluation's auc: 0.836973 [1505] Train's auc: 0.870779 Evaluation's auc: 0.83697 [1506] Train's auc: 0.870789 Evaluation's auc: 0.83697 [1507] Train's auc: 0.870807 Evaluation's auc: 0.836956 [1508] Train's auc: 0.870821 Evaluation's auc: 0.836957 [1509] Train's auc: 0.870831 Evaluation's auc: 0.836943 [1510] Train's auc: 0.870847 Evaluation's auc: 0.836949 [1511] Train's auc: 0.870862 Evaluation's auc: 0.836955 [1512] Train's auc: 0.870876 Evaluation's auc: 0.83696 [1513] Train's auc: 0.870891 Evaluation's auc: 0.836963 [1514] Train's auc: 0.870909 Evaluation's auc: 0.836957 [1515] Train's auc: 0.870923 Evaluation's auc: 0.836963 [1516] Train's auc: 0.870933 Evaluation's auc: 0.836966 [1517] Train's auc: 0.870952 Evaluation's auc: 0.836969 [1518] Train's auc: 0.870966 Evaluation's auc: 0.836979 [1519] Train's auc: 0.870974 Evaluation's auc: 0.836982 [1520] Train's auc: 0.87099 Evaluation's auc: 0.836979 [1521] Train's auc: 0.871003 Evaluation's auc: 0.836975 [1522] Train's auc: 0.871014 Evaluation's auc: 0.836974 [1523] Train's auc: 0.87103 Evaluation's auc: 0.83697 [1524] Train's auc: 0.871042 Evaluation's auc: 0.83697 [1525] Train's auc: 0.871053 Evaluation's auc: 0.836977 [1526] Train's auc: 0.871065 Evaluation's auc: 0.836979 [1527] Train's auc: 0.871072 Evaluation's auc: 0.836987 [1528] Train's auc: 0.87108 Evaluation's auc: 0.836999 [1529] Train's auc: 0.871089 Evaluation's auc: 0.837001 [1530] Train's auc: 0.871102 Evaluation's auc: 0.836989 [1531] Train's auc: 0.871118 Evaluation's auc: 0.836996 [1532] Train's auc: 0.87113 Evaluation's auc: 0.836996 [1533] Train's auc: 0.871143 Evaluation's auc: 0.837009 [1534] Train's auc: 0.871154 Evaluation's auc: 0.837009 [1535] Train's auc: 0.87117 Evaluation's auc: 0.837012 [1536] Train's auc: 0.871178 Evaluation's auc: 0.837003 [1537] Train's auc: 0.871193 Evaluation's auc: 0.837016 [1538] Train's auc: 0.871208 Evaluation's auc: 0.837022 [1539] Train's auc: 0.871227 Evaluation's auc: 0.837012 [1540] Train's auc: 0.871246 Evaluation's auc: 0.837021 [1541] Train's auc: 0.871258 Evaluation's auc: 0.837023 [1542] Train's auc: 0.871278 Evaluation's auc: 0.837016 [1543] Train's auc: 0.871287 Evaluation's auc: 0.837016 [1544] Train's auc: 0.871296 Evaluation's auc: 0.837017 [1545] Train's auc: 0.871312 Evaluation's auc: 0.837021 [1546] Train's auc: 0.871327 Evaluation's auc: 0.837029 [1547] Train's auc: 0.871345 Evaluation's auc: 0.837037 [1548] Train's auc: 0.87136 Evaluation's auc: 0.837038 [1549] Train's auc: 0.871371 Evaluation's auc: 0.837047 [1550] Train's auc: 0.871384 Evaluation's auc: 0.837051 [1551] Train's auc: 0.871398 Evaluation's auc: 0.837061 [1552] Train's auc: 0.871411 Evaluation's auc: 0.837051 [1553] Train's auc: 0.871422 Evaluation's auc: 0.837068 [1554] Train's auc: 0.871434 Evaluation's auc: 0.837062 [1555] Train's auc: 0.871444 Evaluation's auc: 0.837067 [1556] Train's auc: 0.871457 Evaluation's auc: 0.837065 [1557] Train's auc: 0.871474 Evaluation's auc: 0.83707 [1558] Train's auc: 0.871485 Evaluation's auc: 0.837066 [1559] Train's auc: 0.871504 Evaluation's auc: 0.837056 [1560] Train's auc: 0.871518 Evaluation's auc: 0.837054 [1561] Train's auc: 0.871531 Evaluation's auc: 0.837056 [1562] Train's auc: 0.871551 Evaluation's auc: 0.837059 [1563] Train's auc: 0.871559 Evaluation's auc: 0.837051 [1564] Train's auc: 0.871577 Evaluation's auc: 0.837043 [1565] Train's auc: 0.871589 Evaluation's auc: 0.837039 [1566] Train's auc: 0.871601 Evaluation's auc: 0.837039 [1567] Train's auc: 0.87161 Evaluation's auc: 0.837037 [1568] Train's auc: 0.871625 Evaluation's auc: 0.837041 [1569] Train's auc: 0.871631 Evaluation's auc: 0.837037 [1570] Train's auc: 0.871646 Evaluation's auc: 0.837031 [1571] Train's auc: 0.871659 Evaluation's auc: 0.837038 [1572] Train's auc: 0.871677 Evaluation's auc: 0.837034 [1573] Train's auc: 0.871691 Evaluation's auc: 0.837038 [1574] Train's auc: 0.8717 Evaluation's auc: 0.83704 [1575] Train's auc: 0.871713 Evaluation's auc: 0.837047 [1576] Train's auc: 0.871732 Evaluation's auc: 0.837037 [1577] Train's auc: 0.871744 Evaluation's auc: 0.837032 Early stopping, best iteration is: [1557] Train's auc: 0.871474 Evaluation's auc: 0.83707
y_probs_train = gbm_rh.predict(x_train)
y_probs_val = gbm_rh.predict(x_val)
# We can visualize these ROC curves with matplotlib
import matplotlib.pyplot as plt
from sklearn.metrics import confusion_matrix, roc_curve, roc_auc_score
plt.plot(roc_curve(y_train, y_probs_train)[0],roc_curve(y_train, y_probs_train)[1],
color = 'blue', label='Train ROC Curve (area = %0.2f)' % roc_auc_score(y_train, y_probs_train))
plt.plot(roc_curve(y_val, y_probs_val)[0],roc_curve(y_val, y_probs_val)[1],
color = 'red', label='Test ROC Curve (area = %0.2f)' % roc_auc_score(y_val, y_probs_val))
plt.plot([0, 1], [0, 1], color='black', linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.title('AUC-ROC Curve')
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.legend()
plt.show()
import hyperband
from hyperband import HyperbandSearchCV
# Set paramters for the model
band_params = {'boosting_type': 'gbdt',
'class_weight': None,
'colsample_bytree': 0.9,
'importance_type': 'split',
'learning_rate': 0.01,
'max_depth': 20,
'min_child_samples': 25,
'min_split_gain': 0,
'n_estimators': 4000,
'n_jobs': -1,
'num_leaves': 200,
'objective': 'binary',
'random_state': None,
'reg_alpha': 0,
'reg_lambda': 0,
'silent': True,
#'subsample': 0.8,
'subsample_for_bin': 200000,
'subsample_freq': 1,
'metric': 'auc',
'max_bin': 100,
'verbose': -1,
'scale_pos_weight': 1}
param_dict = {
'learning_rate': [.001,0.01,0.1],
'max_depth': [5,15, 20, 30, 50],
'num_leaves': [50,150,200,250],
'min_child_samples': [35,40,60,80],
'subsample': [0.7,0.8,0.9],
'min_child_weight' : [0, 0.5, 2, 3, 5]
}
search = HyperbandSearchCV(lgb.LGBMClassifier(** band_params),param_dict,cv=3,
resource_param='n_estimators',verbose=100,
max_iter=200,min_iter=50,
scoring='roc_auc')
search.fit(x_train,y_train)
Starting bracket 1 (out of 2) of hyperband Starting successive halving iteration 1 out of 2. Fitting 3 configurations, with resource_param n_estimators set to 66, and keeping the best 1 configurations. Fitting 3 folds for each of 3 candidates, totalling 9 fits [Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers. [CV] subsample=0.7, num_leaves=50, min_child_weight=0.5, min_child_samples=80, max_depth=5, learning_rate=0.001, n_estimators=66 [CV] subsample=0.7, num_leaves=50, min_child_weight=0.5, min_child_samples=80, max_depth=5, learning_rate=0.001, n_estimators=66, score=0.792, total= 1.3s [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 1.3s remaining: 0.0s [CV] subsample=0.7, num_leaves=50, min_child_weight=0.5, min_child_samples=80, max_depth=5, learning_rate=0.001, n_estimators=66 [CV] subsample=0.7, num_leaves=50, min_child_weight=0.5, min_child_samples=80, max_depth=5, learning_rate=0.001, n_estimators=66, score=0.797, total= 1.3s [Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 2.6s remaining: 0.0s [CV] subsample=0.7, num_leaves=50, min_child_weight=0.5, min_child_samples=80, max_depth=5, learning_rate=0.001, n_estimators=66 [CV] subsample=0.7, num_leaves=50, min_child_weight=0.5, min_child_samples=80, max_depth=5, learning_rate=0.001, n_estimators=66, score=0.796, total= 1.3s [Parallel(n_jobs=1)]: Done 3 out of 3 | elapsed: 4.0s remaining: 0.0s [CV] subsample=0.7, num_leaves=200, min_child_weight=0, min_child_samples=35, max_depth=5, learning_rate=0.01, n_estimators=66 [CV] subsample=0.7, num_leaves=200, min_child_weight=0, min_child_samples=35, max_depth=5, learning_rate=0.01, n_estimators=66, score=0.800, total= 1.4s [Parallel(n_jobs=1)]: Done 4 out of 4 | elapsed: 5.3s remaining: 0.0s [CV] subsample=0.7, num_leaves=200, min_child_weight=0, min_child_samples=35, max_depth=5, learning_rate=0.01, n_estimators=66 [CV] subsample=0.7, num_leaves=200, min_child_weight=0, min_child_samples=35, max_depth=5, learning_rate=0.01, n_estimators=66, score=0.806, total= 1.3s [Parallel(n_jobs=1)]: Done 5 out of 5 | elapsed: 6.7s remaining: 0.0s [CV] subsample=0.7, num_leaves=200, min_child_weight=0, min_child_samples=35, max_depth=5, learning_rate=0.01, n_estimators=66 [CV] subsample=0.7, num_leaves=200, min_child_weight=0, min_child_samples=35, max_depth=5, learning_rate=0.01, n_estimators=66, score=0.804, total= 1.5s [Parallel(n_jobs=1)]: Done 6 out of 6 | elapsed: 8.2s remaining: 0.0s [CV] subsample=0.7, num_leaves=150, min_child_weight=0.5, min_child_samples=60, max_depth=15, learning_rate=0.1, n_estimators=66 [CV] subsample=0.7, num_leaves=150, min_child_weight=0.5, min_child_samples=60, max_depth=15, learning_rate=0.1, n_estimators=66, score=0.832, total= 2.1s [Parallel(n_jobs=1)]: Done 7 out of 7 | elapsed: 10.3s remaining: 0.0s [CV] subsample=0.7, num_leaves=150, min_child_weight=0.5, min_child_samples=60, max_depth=15, learning_rate=0.1, n_estimators=66 [CV] subsample=0.7, num_leaves=150, min_child_weight=0.5, min_child_samples=60, max_depth=15, learning_rate=0.1, n_estimators=66, score=0.839, total= 2.0s [Parallel(n_jobs=1)]: Done 8 out of 8 | elapsed: 12.3s remaining: 0.0s [CV] subsample=0.7, num_leaves=150, min_child_weight=0.5, min_child_samples=60, max_depth=15, learning_rate=0.1, n_estimators=66 [CV] subsample=0.7, num_leaves=150, min_child_weight=0.5, min_child_samples=60, max_depth=15, learning_rate=0.1, n_estimators=66, score=0.833, total= 2.0s [Parallel(n_jobs=1)]: Done 9 out of 9 | elapsed: 14.3s remaining: 0.0s [Parallel(n_jobs=1)]: Done 9 out of 9 | elapsed: 14.3s finished Starting successive halving iteration 2 out of 2. Fitting 1 configurations, with resource_param n_estimators set to 200 Fitting 3 folds for each of 1 candidates, totalling 3 fits [Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers. [CV] subsample=0.7, num_leaves=150, min_child_weight=0.5, min_child_samples=60, max_depth=15, learning_rate=0.1, n_estimators=200
/Users/piumallick/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:823: FutureWarning: The parameter 'iid' is deprecated in 0.22 and will be removed in 0.24. "removed in 0.24.", FutureWarning
[CV] subsample=0.7, num_leaves=150, min_child_weight=0.5, min_child_samples=60, max_depth=15, learning_rate=0.1, n_estimators=200, score=0.827, total= 4.7s [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 4.7s remaining: 0.0s [CV] subsample=0.7, num_leaves=150, min_child_weight=0.5, min_child_samples=60, max_depth=15, learning_rate=0.1, n_estimators=200 [CV] subsample=0.7, num_leaves=150, min_child_weight=0.5, min_child_samples=60, max_depth=15, learning_rate=0.1, n_estimators=200, score=0.836, total= 4.5s [Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 9.2s remaining: 0.0s [CV] subsample=0.7, num_leaves=150, min_child_weight=0.5, min_child_samples=60, max_depth=15, learning_rate=0.1, n_estimators=200 [CV] subsample=0.7, num_leaves=150, min_child_weight=0.5, min_child_samples=60, max_depth=15, learning_rate=0.1, n_estimators=200, score=0.829, total= 4.5s [Parallel(n_jobs=1)]: Done 3 out of 3 | elapsed: 13.7s remaining: 0.0s [Parallel(n_jobs=1)]: Done 3 out of 3 | elapsed: 13.7s finished Starting bracket 2 (out of 2) of hyperband Starting successive halving iteration 1 out of 1. Fitting 2 configurations, with resource_param n_estimators set to 200 Fitting 3 folds for each of 2 candidates, totalling 6 fits [Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers. [CV] subsample=0.7, num_leaves=200, min_child_weight=0, min_child_samples=80, max_depth=5, learning_rate=0.001, n_estimators=200
/Users/piumallick/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:823: FutureWarning: The parameter 'iid' is deprecated in 0.22 and will be removed in 0.24. "removed in 0.24.", FutureWarning
[CV] subsample=0.7, num_leaves=200, min_child_weight=0, min_child_samples=80, max_depth=5, learning_rate=0.001, n_estimators=200, score=0.795, total= 2.7s [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 2.7s remaining: 0.0s [CV] subsample=0.7, num_leaves=200, min_child_weight=0, min_child_samples=80, max_depth=5, learning_rate=0.001, n_estimators=200 [CV] subsample=0.7, num_leaves=200, min_child_weight=0, min_child_samples=80, max_depth=5, learning_rate=0.001, n_estimators=200, score=0.799, total= 2.7s [Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 5.4s remaining: 0.0s [CV] subsample=0.7, num_leaves=200, min_child_weight=0, min_child_samples=80, max_depth=5, learning_rate=0.001, n_estimators=200 [CV] subsample=0.7, num_leaves=200, min_child_weight=0, min_child_samples=80, max_depth=5, learning_rate=0.001, n_estimators=200, score=0.798, total= 2.7s [Parallel(n_jobs=1)]: Done 3 out of 3 | elapsed: 8.0s remaining: 0.0s [CV] subsample=0.8, num_leaves=50, min_child_weight=0.5, min_child_samples=35, max_depth=5, learning_rate=0.001, n_estimators=200 [CV] subsample=0.8, num_leaves=50, min_child_weight=0.5, min_child_samples=35, max_depth=5, learning_rate=0.001, n_estimators=200, score=0.794, total= 3.0s [Parallel(n_jobs=1)]: Done 4 out of 4 | elapsed: 11.1s remaining: 0.0s [CV] subsample=0.8, num_leaves=50, min_child_weight=0.5, min_child_samples=35, max_depth=5, learning_rate=0.001, n_estimators=200 [CV] subsample=0.8, num_leaves=50, min_child_weight=0.5, min_child_samples=35, max_depth=5, learning_rate=0.001, n_estimators=200, score=0.798, total= 2.9s [Parallel(n_jobs=1)]: Done 5 out of 5 | elapsed: 14.0s remaining: 0.0s [CV] subsample=0.8, num_leaves=50, min_child_weight=0.5, min_child_samples=35, max_depth=5, learning_rate=0.001, n_estimators=200 [CV] subsample=0.8, num_leaves=50, min_child_weight=0.5, min_child_samples=35, max_depth=5, learning_rate=0.001, n_estimators=200, score=0.798, total= 3.1s [Parallel(n_jobs=1)]: Done 6 out of 6 | elapsed: 17.1s remaining: 0.0s [Parallel(n_jobs=1)]: Done 6 out of 6 | elapsed: 17.1s finished
/Users/piumallick/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:823: FutureWarning: The parameter 'iid' is deprecated in 0.22 and will be removed in 0.24. "removed in 0.24.", FutureWarning
HyperbandSearchCV(cv=3, error_score='raise',
estimator=LGBMClassifier(boosting_type='gbdt',
class_weight=None,
colsample_bytree=0.9,
importance_type='split',
learning_rate=0.01, max_bin=100,
max_depth=20, metric='auc',
min_child_samples=25,
min_child_weight=0.001,
min_split_gain=0, n_estimators=4000,
n_jobs=-1, num_leaves=200,
objective='binary',
random_state=None,...
param_distributions={'learning_rate': [0.001, 0.01, 0.1],
'max_depth': [5, 15, 20, 30, 50],
'min_child_samples': [35, 40, 60, 80],
'min_child_weight': [0, 0.5, 2, 3, 5],
'num_leaves': [50, 150, 200, 250],
'subsample': [0.7, 0.8, 0.9]},
pre_dispatch='2*n_jobs', random_state=None, refit=True,
resource_param='n_estimators', return_train_score=False,
scoring='roc_auc', skip_last=0, verbose=100)
search.best_params_
{'subsample': 0.7,
'num_leaves': 150,
'min_child_weight': 0.5,
'min_child_samples': 60,
'max_depth': 15,
'learning_rate': 0.1,
'n_estimators': 66}
band_params = {'subsample': 0.9,
'num_leaves': 200,
'min_child_weight': 0,
'min_child_samples': 80,
'max_depth': 30,
'learning_rate': 0.1,
'n_estimators': 66}
search.cv_results_
{'mean_fit_time': array([1.1687669 , 1.25619014, 1.8475283 , 4.286666 , 2.48585145,
2.83708604]),
'std_fit_time': array([0.02089219, 0.06786707, 0.04141315, 0.08947038, 0.00455839,
0.09006264]),
'mean_score_time': array([0.13999486, 0.1445628 , 0.17552074, 0.274158 , 0.18325957,
0.17965094]),
'std_score_time': array([0.00130434, 0.00329493, 0.00481657, 0.00373901, 0.00464876,
0.00055194]),
'param_subsample': masked_array(data=[0.7, 0.7, 0.7, 0.7, 0.7, 0.8],
mask=[False, False, False, False, False, False],
fill_value='?',
dtype=object),
'param_num_leaves': masked_array(data=[50, 200, 150, 150, 200, 50],
mask=[False, False, False, False, False, False],
fill_value='?',
dtype=object),
'param_min_child_weight': masked_array(data=[0.5, 0, 0.5, 0.5, 0, 0.5],
mask=[False, False, False, False, False, False],
fill_value='?',
dtype=object),
'param_min_child_samples': masked_array(data=[80, 35, 60, 60, 80, 35],
mask=[False, False, False, False, False, False],
fill_value='?',
dtype=object),
'param_max_depth': masked_array(data=[5, 5, 15, 15, 5, 5],
mask=[False, False, False, False, False, False],
fill_value='?',
dtype=object),
'param_learning_rate': masked_array(data=[0.001, 0.01, 0.1, 0.1, 0.001, 0.001],
mask=[False, False, False, False, False, False],
fill_value='?',
dtype=object),
'param_n_estimators': masked_array(data=[66, 66, 66, 200, 200, 200],
mask=[False, False, False, False, False, False],
fill_value='?',
dtype=object),
'params': [{'subsample': 0.7,
'num_leaves': 50,
'min_child_weight': 0.5,
'min_child_samples': 80,
'max_depth': 5,
'learning_rate': 0.001,
'n_estimators': 66},
{'subsample': 0.7,
'num_leaves': 200,
'min_child_weight': 0,
'min_child_samples': 35,
'max_depth': 5,
'learning_rate': 0.01,
'n_estimators': 66},
{'subsample': 0.7,
'num_leaves': 150,
'min_child_weight': 0.5,
'min_child_samples': 60,
'max_depth': 15,
'learning_rate': 0.1,
'n_estimators': 66},
{'subsample': 0.7,
'num_leaves': 150,
'min_child_weight': 0.5,
'min_child_samples': 60,
'max_depth': 15,
'learning_rate': 0.1,
'n_estimators': 200},
{'subsample': 0.7,
'num_leaves': 200,
'min_child_weight': 0,
'min_child_samples': 80,
'max_depth': 5,
'learning_rate': 0.001,
'n_estimators': 200},
{'subsample': 0.8,
'num_leaves': 50,
'min_child_weight': 0.5,
'min_child_samples': 35,
'max_depth': 5,
'learning_rate': 0.001,
'n_estimators': 200}],
'split0_test_score': array([0.79226019, 0.79973459, 0.83238271, 0.82717367, 0.79451763,
0.79391491]),
'split1_test_score': array([0.79718138, 0.80639349, 0.83885198, 0.83623924, 0.79928345,
0.79823213]),
'split2_test_score': array([0.79629067, 0.80356313, 0.83292964, 0.82879948, 0.79829625,
0.79782653]),
'mean_test_score': array([0.79524406, 0.8032304 , 0.83472148, 0.8307375 , 0.79736576,
0.79665783]),
'std_test_score': array([0.00214105, 0.00272867, 0.00292927, 0.00394658, 0.00205389,
0.00194662]),
'rank_test_score': array([6, 3, 1, 2, 4, 5], dtype=int32),
'hyperband_bracket': array([1., 1., 1., 1., 2., 2.])}
## Predicting the data
search.score(x_train, y_train)
0.9477880595150036
search.score(x_test, y_test)
0.8375628226678985
# Sets the space to search over and the prior probabilities over the search space
lgbm_space = {
# hp.choice.choice will select 1 value from the given list , 'dart', 'goss', 'rf'
'boosting_type': hp.hp.choice('boosting_type', ['gbdt']),
'objective': hp.hp.choice('objective', ['binary']),
'num_leaves':hp.hp.choice('num_leaves', np.arange(10, 100,1, dtype=int)),
'subsample':hp.hp.quniform('subsample',0.5,1.0,0.05),
'colsample_bytree':hp.hp.quniform('colsample_bytree',0.5,1.0,0.05),
'min_child_weight':hp.hp.quniform('min_child_weight', 100, 1000,100),
'lambda_l1': hp.hp.uniform('lambda_l1', 0.0, 1000.0),
'lambda_l2': hp.hp.uniform('lambda_l2', 0.0, 1000.0),
'learning_rate': hp.hp.loguniform('learning_rate', -4, 0),
'feature_fraction': hp.hp.loguniform('feature_fraction', -4, 0),
'bagging_fraction': hp.hp.loguniform('bagging_fraction', -4, 0),
'bagging_frequency':hp.hp.choice('bagging_frequency', np.arange(5, 100,1, dtype=int)),
'drop_rate': hp.hp.loguniform('drop_rate', -4, 0),
'scale_pos_weight': hp.hp.uniform('scale_pos_weight', 6.0, 10.0),
'metric' : hp.hp.choice('metric', ['auc']),
'max_depth': hp.hp.choice('max_depth', np.arange(1, 100,1, dtype=int))
}
# Here we define an objective (loss) function I take
def objective_m(params, n_folds=5):
model = lgb.cv(params = params,
train_set = lgb_proc_train_rh,
num_boost_round = 10000,
early_stopping_rounds = 10,
nfold = n_folds)
# returns the best average loss on validation set
#print(model)
loss = 1-(max(model['auc-mean']))
return loss
bayes_trials = Trials()
MAX_EVALS = 100 # this controls the runtime
lgbm_best_m = fmin(fn = objective_m, space = lgbm_space, algo = hp.tpe.suggest,
max_evals = MAX_EVALS, trials = bayes_trials)
100%|██████████| 100/100 [09:11<00:00, 5.51s/trial, best loss: 0.1574320283879065]
lgbm_best_m
{'bagging_fraction': 0.04690582606565,
'bagging_frequency': 27,
'boosting_type': 0,
'colsample_bytree': 0.6000000000000001,
'drop_rate': 0.05448125188564363,
'feature_fraction': 0.42721382915764394,
'lambda_l1': 2.409364745534752,
'lambda_l2': 210.22831642617797,
'learning_rate': 0.31014578499166295,
'max_depth': 74,
'metric': 0,
'min_child_weight': 100.0,
'num_leaves': 77,
'objective': 0,
'scale_pos_weight': 8.258766413767718,
'subsample': 0.9}
lgb_params2 = {'bagging_fraction': 0.4584000884522912,
'bagging_frequency': 75,
'boosting_type': 'gbdt',
'metric': 'auc',
'colsample_bytree': 0.8,
'drop_rate': 0.28657769218383206,
'feature_fraction': 0.06676229703625178,
'lambda_l1': 3.7177635273122966,
'lambda_l2': 694.9058177271635,
'learning_rate': 0.1504837141507504,
'max_depth': 40,
'min_child_weight': 100.0,
'num_leaves': 51,
'scale_pos_weight': 7.4503069212775985,
'subsample': 0.9
}
gbm_rh2 = lgb.train(params = lgb_params2, train_set = lgb_proc_train_rh,
num_boost_round = 5000, valid_sets = [lgb_proc_val_rh, lgb_proc_train_rh],
valid_names = ['Evaluation', 'Train'])
[1] Train's auc: 0.636951 Evaluation's auc: 0.629649 [2] Train's auc: 0.703514 Evaluation's auc: 0.689602 [3] Train's auc: 0.724583 Evaluation's auc: 0.712357 [4] Train's auc: 0.7584 Evaluation's auc: 0.743413 [5] Train's auc: 0.758036 Evaluation's auc: 0.742912 [6] Train's auc: 0.76326 Evaluation's auc: 0.749456 [7] Train's auc: 0.794212 Evaluation's auc: 0.782233 [8] Train's auc: 0.799726 Evaluation's auc: 0.787347 [9] Train's auc: 0.800631 Evaluation's auc: 0.787874 [10] Train's auc: 0.802235 Evaluation's auc: 0.790893 [11] Train's auc: 0.801542 Evaluation's auc: 0.789616 [12] Train's auc: 0.800436 Evaluation's auc: 0.788491 [13] Train's auc: 0.800616 Evaluation's auc: 0.787924 [14] Train's auc: 0.815324 Evaluation's auc: 0.802295 [15] Train's auc: 0.814743 Evaluation's auc: 0.801433 [16] Train's auc: 0.814185 Evaluation's auc: 0.800664 [17] Train's auc: 0.813833 Evaluation's auc: 0.800166 [18] Train's auc: 0.813344 Evaluation's auc: 0.799011 [19] Train's auc: 0.813218 Evaluation's auc: 0.798748 [20] Train's auc: 0.812069 Evaluation's auc: 0.797858 [21] Train's auc: 0.812655 Evaluation's auc: 0.797689 [22] Train's auc: 0.817537 Evaluation's auc: 0.802173 [23] Train's auc: 0.824544 Evaluation's auc: 0.809298 [24] Train's auc: 0.829867 Evaluation's auc: 0.814076 [25] Train's auc: 0.833839 Evaluation's auc: 0.817741 [26] Train's auc: 0.834272 Evaluation's auc: 0.818175 [27] Train's auc: 0.834381 Evaluation's auc: 0.8181 [28] Train's auc: 0.83512 Evaluation's auc: 0.818281 [29] Train's auc: 0.835725 Evaluation's auc: 0.818504 [30] Train's auc: 0.836014 Evaluation's auc: 0.81854 [31] Train's auc: 0.836079 Evaluation's auc: 0.818509 [32] Train's auc: 0.836634 Evaluation's auc: 0.81865 [33] Train's auc: 0.837196 Evaluation's auc: 0.819024 [34] Train's auc: 0.837762 Evaluation's auc: 0.81928 [35] Train's auc: 0.838329 Evaluation's auc: 0.81945 [36] Train's auc: 0.838825 Evaluation's auc: 0.819662 [37] Train's auc: 0.839257 Evaluation's auc: 0.819814 [38] Train's auc: 0.839541 Evaluation's auc: 0.819849 [39] Train's auc: 0.839757 Evaluation's auc: 0.81994 [40] Train's auc: 0.840933 Evaluation's auc: 0.820849 [41] Train's auc: 0.840854 Evaluation's auc: 0.820686 [42] Train's auc: 0.841132 Evaluation's auc: 0.820574 [43] Train's auc: 0.841478 Evaluation's auc: 0.821026 [44] Train's auc: 0.841639 Evaluation's auc: 0.821064 [45] Train's auc: 0.842001 Evaluation's auc: 0.821152 [46] Train's auc: 0.842 Evaluation's auc: 0.821085 [47] Train's auc: 0.842372 Evaluation's auc: 0.821094 [48] Train's auc: 0.84296 Evaluation's auc: 0.821263 [49] Train's auc: 0.844149 Evaluation's auc: 0.822157 [50] Train's auc: 0.844149 Evaluation's auc: 0.822112 [51] Train's auc: 0.844519 Evaluation's auc: 0.82205 [52] Train's auc: 0.844729 Evaluation's auc: 0.82208 [53] Train's auc: 0.845185 Evaluation's auc: 0.822168 [54] Train's auc: 0.845467 Evaluation's auc: 0.822414 [55] Train's auc: 0.845684 Evaluation's auc: 0.822545 [56] Train's auc: 0.846209 Evaluation's auc: 0.82295 [57] Train's auc: 0.846838 Evaluation's auc: 0.823406 [58] Train's auc: 0.847131 Evaluation's auc: 0.823508 [59] Train's auc: 0.848038 Evaluation's auc: 0.824024 [60] Train's auc: 0.848422 Evaluation's auc: 0.824149 [61] Train's auc: 0.848735 Evaluation's auc: 0.824082 [62] Train's auc: 0.848911 Evaluation's auc: 0.824093 [63] Train's auc: 0.84905 Evaluation's auc: 0.824035 [64] Train's auc: 0.851456 Evaluation's auc: 0.826905 [65] Train's auc: 0.851567 Evaluation's auc: 0.82693 [66] Train's auc: 0.851947 Evaluation's auc: 0.827122 [67] Train's auc: 0.853692 Evaluation's auc: 0.828835 [68] Train's auc: 0.855113 Evaluation's auc: 0.830507 [69] Train's auc: 0.855383 Evaluation's auc: 0.830482 [70] Train's auc: 0.855739 Evaluation's auc: 0.830699 [71] Train's auc: 0.856157 Evaluation's auc: 0.830837 [72] Train's auc: 0.856226 Evaluation's auc: 0.830938 [73] Train's auc: 0.856736 Evaluation's auc: 0.831198 [74] Train's auc: 0.857126 Evaluation's auc: 0.831463 [75] Train's auc: 0.857422 Evaluation's auc: 0.831583 [76] Train's auc: 0.857871 Evaluation's auc: 0.831625 [77] Train's auc: 0.858285 Evaluation's auc: 0.831829 [78] Train's auc: 0.858593 Evaluation's auc: 0.831754 [79] Train's auc: 0.858994 Evaluation's auc: 0.831857 [80] Train's auc: 0.859282 Evaluation's auc: 0.831816 [81] Train's auc: 0.859684 Evaluation's auc: 0.831993 [82] Train's auc: 0.859852 Evaluation's auc: 0.832231 [83] Train's auc: 0.859963 Evaluation's auc: 0.832313 [84] Train's auc: 0.860151 Evaluation's auc: 0.832365 [85] Train's auc: 0.860685 Evaluation's auc: 0.832408 [86] Train's auc: 0.86092 Evaluation's auc: 0.83242 [87] Train's auc: 0.861179 Evaluation's auc: 0.832361 [88] Train's auc: 0.861533 Evaluation's auc: 0.832389 [89] Train's auc: 0.861744 Evaluation's auc: 0.8323 [90] Train's auc: 0.862078 Evaluation's auc: 0.832437 [91] Train's auc: 0.862187 Evaluation's auc: 0.832456 [92] Train's auc: 0.863109 Evaluation's auc: 0.833435 [93] Train's auc: 0.863331 Evaluation's auc: 0.833619 [94] Train's auc: 0.863691 Evaluation's auc: 0.833746 [95] Train's auc: 0.863972 Evaluation's auc: 0.833705 [96] Train's auc: 0.864475 Evaluation's auc: 0.833906 [97] Train's auc: 0.864532 Evaluation's auc: 0.833859 [98] Train's auc: 0.864755 Evaluation's auc: 0.833892 [99] Train's auc: 0.864756 Evaluation's auc: 0.833833 [100] Train's auc: 0.865151 Evaluation's auc: 0.833899 [101] Train's auc: 0.865347 Evaluation's auc: 0.83376 [102] Train's auc: 0.865685 Evaluation's auc: 0.833949 [103] Train's auc: 0.865976 Evaluation's auc: 0.833955 [104] Train's auc: 0.866421 Evaluation's auc: 0.834092 [105] Train's auc: 0.866743 Evaluation's auc: 0.834168 [106] Train's auc: 0.866971 Evaluation's auc: 0.834223 [107] Train's auc: 0.867046 Evaluation's auc: 0.834225 [108] Train's auc: 0.867471 Evaluation's auc: 0.834359 [109] Train's auc: 0.867721 Evaluation's auc: 0.834382 [110] Train's auc: 0.867986 Evaluation's auc: 0.834386 [111] Train's auc: 0.868244 Evaluation's auc: 0.834392 [112] Train's auc: 0.868524 Evaluation's auc: 0.834399 [113] Train's auc: 0.868779 Evaluation's auc: 0.834422 [114] Train's auc: 0.869146 Evaluation's auc: 0.834437 [115] Train's auc: 0.869429 Evaluation's auc: 0.834676 [116] Train's auc: 0.869717 Evaluation's auc: 0.834677 [117] Train's auc: 0.869884 Evaluation's auc: 0.834693 [118] Train's auc: 0.870763 Evaluation's auc: 0.835696 [119] Train's auc: 0.87108 Evaluation's auc: 0.83581 [120] Train's auc: 0.871748 Evaluation's auc: 0.83661 [121] Train's auc: 0.872016 Evaluation's auc: 0.836827 [122] Train's auc: 0.872308 Evaluation's auc: 0.836917 [123] Train's auc: 0.872522 Evaluation's auc: 0.836912 [124] Train's auc: 0.872751 Evaluation's auc: 0.836892 [125] Train's auc: 0.872873 Evaluation's auc: 0.836884 [126] Train's auc: 0.873154 Evaluation's auc: 0.836829 [127] Train's auc: 0.873423 Evaluation's auc: 0.836976 [128] Train's auc: 0.87365 Evaluation's auc: 0.836953 [129] Train's auc: 0.873904 Evaluation's auc: 0.836978 [130] Train's auc: 0.874123 Evaluation's auc: 0.836944 [131] Train's auc: 0.874371 Evaluation's auc: 0.836947 [132] Train's auc: 0.874507 Evaluation's auc: 0.836977 [133] Train's auc: 0.874742 Evaluation's auc: 0.836881 [134] Train's auc: 0.875234 Evaluation's auc: 0.837219 [135] Train's auc: 0.875444 Evaluation's auc: 0.837189 [136] Train's auc: 0.875593 Evaluation's auc: 0.837238 [137] Train's auc: 0.875775 Evaluation's auc: 0.837209 [138] Train's auc: 0.876096 Evaluation's auc: 0.837288 [139] Train's auc: 0.876178 Evaluation's auc: 0.837303 [140] Train's auc: 0.876604 Evaluation's auc: 0.837896 [141] Train's auc: 0.876758 Evaluation's auc: 0.837875 [142] Train's auc: 0.877036 Evaluation's auc: 0.838003 [143] Train's auc: 0.877282 Evaluation's auc: 0.838102 [144] Train's auc: 0.877625 Evaluation's auc: 0.838103 [145] Train's auc: 0.877855 Evaluation's auc: 0.838112 [146] Train's auc: 0.878007 Evaluation's auc: 0.838193 [147] Train's auc: 0.878119 Evaluation's auc: 0.83813 [148] Train's auc: 0.878375 Evaluation's auc: 0.838147 [149] Train's auc: 0.878579 Evaluation's auc: 0.838132 [150] Train's auc: 0.87883 Evaluation's auc: 0.838295 [151] Train's auc: 0.87906 Evaluation's auc: 0.838285 [152] Train's auc: 0.879215 Evaluation's auc: 0.838376 [153] Train's auc: 0.87948 Evaluation's auc: 0.838378 [154] Train's auc: 0.879725 Evaluation's auc: 0.838416 [155] Train's auc: 0.879927 Evaluation's auc: 0.838273 [156] Train's auc: 0.880103 Evaluation's auc: 0.838302 [157] Train's auc: 0.880249 Evaluation's auc: 0.838351 [158] Train's auc: 0.88043 Evaluation's auc: 0.838298 [159] Train's auc: 0.880706 Evaluation's auc: 0.838288 [160] Train's auc: 0.880897 Evaluation's auc: 0.838317 [161] Train's auc: 0.881186 Evaluation's auc: 0.838281 [162] Train's auc: 0.881506 Evaluation's auc: 0.838369 [163] Train's auc: 0.881681 Evaluation's auc: 0.838444 [164] Train's auc: 0.88186 Evaluation's auc: 0.838517 [165] Train's auc: 0.882101 Evaluation's auc: 0.838548 [166] Train's auc: 0.88234 Evaluation's auc: 0.838594 [167] Train's auc: 0.88254 Evaluation's auc: 0.83857 [168] Train's auc: 0.882802 Evaluation's auc: 0.838644 [169] Train's auc: 0.883033 Evaluation's auc: 0.838657 [170] Train's auc: 0.883146 Evaluation's auc: 0.838657 [171] Train's auc: 0.883287 Evaluation's auc: 0.838674 [172] Train's auc: 0.883522 Evaluation's auc: 0.838746 [173] Train's auc: 0.883675 Evaluation's auc: 0.838735 [174] Train's auc: 0.883879 Evaluation's auc: 0.838839 [175] Train's auc: 0.884049 Evaluation's auc: 0.8389 [176] Train's auc: 0.88451 Evaluation's auc: 0.83949 [177] Train's auc: 0.884732 Evaluation's auc: 0.839537 [178] Train's auc: 0.884922 Evaluation's auc: 0.839479 [179] Train's auc: 0.885109 Evaluation's auc: 0.839367 [180] Train's auc: 0.885347 Evaluation's auc: 0.839444 [181] Train's auc: 0.885536 Evaluation's auc: 0.839404 [182] Train's auc: 0.885636 Evaluation's auc: 0.839386 [183] Train's auc: 0.885773 Evaluation's auc: 0.839372 [184] Train's auc: 0.885881 Evaluation's auc: 0.839397 [185] Train's auc: 0.88604 Evaluation's auc: 0.839334 [186] Train's auc: 0.886232 Evaluation's auc: 0.839422 [187] Train's auc: 0.886408 Evaluation's auc: 0.839428 [188] Train's auc: 0.886577 Evaluation's auc: 0.839427 [189] Train's auc: 0.886855 Evaluation's auc: 0.839519 [190] Train's auc: 0.887018 Evaluation's auc: 0.839715 [191] Train's auc: 0.887134 Evaluation's auc: 0.839644 [192] Train's auc: 0.887321 Evaluation's auc: 0.839619 [193] Train's auc: 0.887536 Evaluation's auc: 0.839654 [194] Train's auc: 0.88774 Evaluation's auc: 0.839611 [195] Train's auc: 0.887924 Evaluation's auc: 0.839643 [196] Train's auc: 0.888149 Evaluation's auc: 0.8397 [197] Train's auc: 0.888331 Evaluation's auc: 0.839678 [198] Train's auc: 0.888566 Evaluation's auc: 0.839794 [199] Train's auc: 0.888749 Evaluation's auc: 0.839736 [200] Train's auc: 0.888933 Evaluation's auc: 0.839771 [201] Train's auc: 0.889043 Evaluation's auc: 0.839781 [202] Train's auc: 0.889268 Evaluation's auc: 0.839732 [203] Train's auc: 0.889446 Evaluation's auc: 0.839687 [204] Train's auc: 0.889691 Evaluation's auc: 0.839596 [205] Train's auc: 0.889839 Evaluation's auc: 0.839608 [206] Train's auc: 0.890025 Evaluation's auc: 0.839633 [207] Train's auc: 0.890113 Evaluation's auc: 0.839664 [208] Train's auc: 0.890204 Evaluation's auc: 0.839711 [209] Train's auc: 0.8904 Evaluation's auc: 0.839799 [210] Train's auc: 0.89049 Evaluation's auc: 0.839717 [211] Train's auc: 0.890677 Evaluation's auc: 0.839702 [212] Train's auc: 0.891038 Evaluation's auc: 0.840132 [213] Train's auc: 0.891241 Evaluation's auc: 0.840166 [214] Train's auc: 0.891397 Evaluation's auc: 0.840176 [215] Train's auc: 0.891651 Evaluation's auc: 0.84053 [216] Train's auc: 0.891874 Evaluation's auc: 0.840458 [217] Train's auc: 0.891904 Evaluation's auc: 0.840473 [218] Train's auc: 0.892043 Evaluation's auc: 0.840457 [219] Train's auc: 0.892149 Evaluation's auc: 0.840449 [220] Train's auc: 0.892309 Evaluation's auc: 0.840387 [221] Train's auc: 0.892526 Evaluation's auc: 0.840431 [222] Train's auc: 0.892719 Evaluation's auc: 0.840327 [223] Train's auc: 0.892919 Evaluation's auc: 0.840302 [224] Train's auc: 0.892983 Evaluation's auc: 0.840304 [225] Train's auc: 0.89311 Evaluation's auc: 0.840311 [226] Train's auc: 0.893213 Evaluation's auc: 0.840284 [227] Train's auc: 0.893356 Evaluation's auc: 0.840317 [228] Train's auc: 0.893552 Evaluation's auc: 0.840225 [229] Train's auc: 0.893729 Evaluation's auc: 0.840236 [230] Train's auc: 0.893896 Evaluation's auc: 0.840286 [231] Train's auc: 0.894057 Evaluation's auc: 0.840304 [232] Train's auc: 0.894168 Evaluation's auc: 0.840354 [233] Train's auc: 0.89442 Evaluation's auc: 0.84038 [234] Train's auc: 0.894569 Evaluation's auc: 0.840366 [235] Train's auc: 0.894741 Evaluation's auc: 0.840306 [236] Train's auc: 0.894947 Evaluation's auc: 0.840285 [237] Train's auc: 0.895058 Evaluation's auc: 0.840346 [238] Train's auc: 0.895221 Evaluation's auc: 0.840339 [239] Train's auc: 0.895279 Evaluation's auc: 0.84038 [240] Train's auc: 0.895442 Evaluation's auc: 0.840372 [241] Train's auc: 0.895648 Evaluation's auc: 0.840752 [242] Train's auc: 0.895783 Evaluation's auc: 0.840758 [243] Train's auc: 0.895883 Evaluation's auc: 0.840681 [244] Train's auc: 0.896102 Evaluation's auc: 0.840646 [245] Train's auc: 0.89629 Evaluation's auc: 0.840668 [246] Train's auc: 0.896433 Evaluation's auc: 0.840703 [247] Train's auc: 0.89664 Evaluation's auc: 0.840675 [248] Train's auc: 0.896802 Evaluation's auc: 0.840696 [249] Train's auc: 0.896972 Evaluation's auc: 0.840693 [250] Train's auc: 0.897126 Evaluation's auc: 0.840691 [251] Train's auc: 0.897265 Evaluation's auc: 0.840739 [252] Train's auc: 0.897427 Evaluation's auc: 0.84086 [253] Train's auc: 0.89763 Evaluation's auc: 0.840867 [254] Train's auc: 0.897707 Evaluation's auc: 0.840897 [255] Train's auc: 0.897856 Evaluation's auc: 0.840849 [256] Train's auc: 0.898116 Evaluation's auc: 0.840982 [257] Train's auc: 0.898278 Evaluation's auc: 0.841054 [258] Train's auc: 0.898398 Evaluation's auc: 0.841048 [259] Train's auc: 0.898547 Evaluation's auc: 0.841056 [260] Train's auc: 0.898657 Evaluation's auc: 0.841169 [261] Train's auc: 0.898877 Evaluation's auc: 0.841178 [262] Train's auc: 0.899072 Evaluation's auc: 0.841145 [263] Train's auc: 0.899245 Evaluation's auc: 0.841102 [264] Train's auc: 0.899495 Evaluation's auc: 0.841267 [265] Train's auc: 0.899697 Evaluation's auc: 0.841249 [266] Train's auc: 0.899941 Evaluation's auc: 0.841145 [267] Train's auc: 0.900042 Evaluation's auc: 0.84115 [268] Train's auc: 0.900158 Evaluation's auc: 0.841102 [269] Train's auc: 0.90028 Evaluation's auc: 0.841074 [270] Train's auc: 0.900379 Evaluation's auc: 0.841102 [271] Train's auc: 0.90047 Evaluation's auc: 0.841109 [272] Train's auc: 0.900631 Evaluation's auc: 0.841018 [273] Train's auc: 0.900791 Evaluation's auc: 0.841066 [274] Train's auc: 0.900869 Evaluation's auc: 0.841047 [275] Train's auc: 0.901015 Evaluation's auc: 0.841045 [276] Train's auc: 0.901186 Evaluation's auc: 0.841157 [277] Train's auc: 0.901307 Evaluation's auc: 0.841179 [278] Train's auc: 0.901435 Evaluation's auc: 0.84119 [279] Train's auc: 0.901557 Evaluation's auc: 0.841191 [280] Train's auc: 0.901706 Evaluation's auc: 0.841212 [281] Train's auc: 0.901875 Evaluation's auc: 0.841207 [282] Train's auc: 0.902027 Evaluation's auc: 0.84144 [283] Train's auc: 0.902162 Evaluation's auc: 0.84146 [284] Train's auc: 0.902263 Evaluation's auc: 0.841412 [285] Train's auc: 0.90243 Evaluation's auc: 0.841447 [286] Train's auc: 0.90255 Evaluation's auc: 0.841431 [287] Train's auc: 0.902743 Evaluation's auc: 0.841412 [288] Train's auc: 0.9029 Evaluation's auc: 0.841394 [289] Train's auc: 0.903076 Evaluation's auc: 0.841308 [290] Train's auc: 0.903236 Evaluation's auc: 0.841377 [291] Train's auc: 0.903483 Evaluation's auc: 0.841618 [292] Train's auc: 0.903564 Evaluation's auc: 0.841603 [293] Train's auc: 0.903679 Evaluation's auc: 0.841594 [294] Train's auc: 0.903706 Evaluation's auc: 0.841598 [295] Train's auc: 0.903784 Evaluation's auc: 0.841609 [296] Train's auc: 0.903902 Evaluation's auc: 0.841774 [297] Train's auc: 0.903978 Evaluation's auc: 0.841786 [298] Train's auc: 0.904183 Evaluation's auc: 0.841751 [299] Train's auc: 0.904326 Evaluation's auc: 0.841791 [300] Train's auc: 0.904427 Evaluation's auc: 0.841874 [301] Train's auc: 0.904578 Evaluation's auc: 0.841847 [302] Train's auc: 0.904738 Evaluation's auc: 0.841829 [303] Train's auc: 0.904904 Evaluation's auc: 0.841779 [304] Train's auc: 0.904981 Evaluation's auc: 0.84181 [305] Train's auc: 0.905111 Evaluation's auc: 0.841761 [306] Train's auc: 0.905208 Evaluation's auc: 0.841776 [307] Train's auc: 0.905357 Evaluation's auc: 0.841795 [308] Train's auc: 0.905499 Evaluation's auc: 0.841955 [309] Train's auc: 0.905569 Evaluation's auc: 0.841933 [310] Train's auc: 0.905696 Evaluation's auc: 0.841949 [311] Train's auc: 0.905842 Evaluation's auc: 0.841947 [312] Train's auc: 0.906017 Evaluation's auc: 0.842011 [313] Train's auc: 0.906127 Evaluation's auc: 0.841987 [314] Train's auc: 0.906343 Evaluation's auc: 0.84205 [315] Train's auc: 0.906416 Evaluation's auc: 0.842085 [316] Train's auc: 0.90655 Evaluation's auc: 0.842088 [317] Train's auc: 0.906695 Evaluation's auc: 0.842078 [318] Train's auc: 0.906817 Evaluation's auc: 0.842006 [319] Train's auc: 0.906987 Evaluation's auc: 0.841898 [320] Train's auc: 0.907013 Evaluation's auc: 0.841916 [321] Train's auc: 0.907147 Evaluation's auc: 0.841904 [322] Train's auc: 0.907301 Evaluation's auc: 0.841894 [323] Train's auc: 0.907413 Evaluation's auc: 0.841914 [324] Train's auc: 0.907544 Evaluation's auc: 0.841957 [325] Train's auc: 0.907597 Evaluation's auc: 0.841956 [326] Train's auc: 0.907761 Evaluation's auc: 0.841878 [327] Train's auc: 0.907922 Evaluation's auc: 0.841898 [328] Train's auc: 0.908092 Evaluation's auc: 0.841883 [329] Train's auc: 0.908239 Evaluation's auc: 0.841873 [330] Train's auc: 0.908363 Evaluation's auc: 0.84183 [331] Train's auc: 0.908514 Evaluation's auc: 0.84187 [332] Train's auc: 0.908692 Evaluation's auc: 0.84192 [333] Train's auc: 0.90876 Evaluation's auc: 0.841878 [334] Train's auc: 0.908866 Evaluation's auc: 0.841825 [335] Train's auc: 0.90904 Evaluation's auc: 0.841847 [336] Train's auc: 0.90913 Evaluation's auc: 0.841801 [337] Train's auc: 0.909268 Evaluation's auc: 0.841798 [338] Train's auc: 0.909393 Evaluation's auc: 0.841909 [339] Train's auc: 0.909635 Evaluation's auc: 0.842012 [340] Train's auc: 0.909767 Evaluation's auc: 0.841998 [341] Train's auc: 0.909863 Evaluation's auc: 0.842039 [342] Train's auc: 0.909975 Evaluation's auc: 0.842005 [343] Train's auc: 0.910125 Evaluation's auc: 0.842155 [344] Train's auc: 0.910268 Evaluation's auc: 0.842191 [345] Train's auc: 0.910314 Evaluation's auc: 0.842163 [346] Train's auc: 0.910443 Evaluation's auc: 0.842135 [347] Train's auc: 0.910561 Evaluation's auc: 0.842151 [348] Train's auc: 0.910778 Evaluation's auc: 0.842483 [349] Train's auc: 0.910872 Evaluation's auc: 0.842458 [350] Train's auc: 0.910962 Evaluation's auc: 0.842453 [351] Train's auc: 0.91106 Evaluation's auc: 0.842454 [352] Train's auc: 0.911173 Evaluation's auc: 0.842427 [353] Train's auc: 0.91138 Evaluation's auc: 0.842554 [354] Train's auc: 0.911532 Evaluation's auc: 0.84258 [355] Train's auc: 0.911581 Evaluation's auc: 0.842573 [356] Train's auc: 0.911711 Evaluation's auc: 0.842626 [357] Train's auc: 0.911854 Evaluation's auc: 0.842637 [358] Train's auc: 0.911974 Evaluation's auc: 0.842674 [359] Train's auc: 0.912082 Evaluation's auc: 0.842572 [360] Train's auc: 0.91222 Evaluation's auc: 0.842552 [361] Train's auc: 0.912354 Evaluation's auc: 0.842519 [362] Train's auc: 0.912498 Evaluation's auc: 0.842513 [363] Train's auc: 0.912645 Evaluation's auc: 0.842491 [364] Train's auc: 0.912829 Evaluation's auc: 0.84251 [365] Train's auc: 0.913 Evaluation's auc: 0.842551 [366] Train's auc: 0.913117 Evaluation's auc: 0.842512 [367] Train's auc: 0.913235 Evaluation's auc: 0.842532 [368] Train's auc: 0.913362 Evaluation's auc: 0.842515 [369] Train's auc: 0.913479 Evaluation's auc: 0.842512 [370] Train's auc: 0.913595 Evaluation's auc: 0.84243 [371] Train's auc: 0.913703 Evaluation's auc: 0.842464 [372] Train's auc: 0.913828 Evaluation's auc: 0.842463 [373] Train's auc: 0.91395 Evaluation's auc: 0.842434 [374] Train's auc: 0.914082 Evaluation's auc: 0.84241 [375] Train's auc: 0.914174 Evaluation's auc: 0.842398 [376] Train's auc: 0.914259 Evaluation's auc: 0.842345 [377] Train's auc: 0.914385 Evaluation's auc: 0.842333 [378] Train's auc: 0.914508 Evaluation's auc: 0.8423 [379] Train's auc: 0.914624 Evaluation's auc: 0.842258 [380] Train's auc: 0.914744 Evaluation's auc: 0.842187 [381] Train's auc: 0.914823 Evaluation's auc: 0.842184 [382] Train's auc: 0.914931 Evaluation's auc: 0.842253 [383] Train's auc: 0.914989 Evaluation's auc: 0.842227 [384] Train's auc: 0.915116 Evaluation's auc: 0.842195 [385] Train's auc: 0.915225 Evaluation's auc: 0.842137 [386] Train's auc: 0.915369 Evaluation's auc: 0.84214 [387] Train's auc: 0.915422 Evaluation's auc: 0.84213 [388] Train's auc: 0.915559 Evaluation's auc: 0.842114 [389] Train's auc: 0.915704 Evaluation's auc: 0.842124 [390] Train's auc: 0.915868 Evaluation's auc: 0.842144 [391] Train's auc: 0.915913 Evaluation's auc: 0.842144 [392] Train's auc: 0.915988 Evaluation's auc: 0.84214 [393] Train's auc: 0.916045 Evaluation's auc: 0.842177 [394] Train's auc: 0.916124 Evaluation's auc: 0.842167 [395] Train's auc: 0.916304 Evaluation's auc: 0.842213 [396] Train's auc: 0.91637 Evaluation's auc: 0.842249 [397] Train's auc: 0.916486 Evaluation's auc: 0.842215 [398] Train's auc: 0.916538 Evaluation's auc: 0.842231 [399] Train's auc: 0.916619 Evaluation's auc: 0.842255 [400] Train's auc: 0.916661 Evaluation's auc: 0.842255 [401] Train's auc: 0.916738 Evaluation's auc: 0.84225 [402] Train's auc: 0.916861 Evaluation's auc: 0.842185 [403] Train's auc: 0.916973 Evaluation's auc: 0.842146 [404] Train's auc: 0.917067 Evaluation's auc: 0.842125 [405] Train's auc: 0.917122 Evaluation's auc: 0.842106 [406] Train's auc: 0.917244 Evaluation's auc: 0.842093 [407] Train's auc: 0.917382 Evaluation's auc: 0.842056 [408] Train's auc: 0.917447 Evaluation's auc: 0.84203 [409] Train's auc: 0.917532 Evaluation's auc: 0.84198 [410] Train's auc: 0.917664 Evaluation's auc: 0.84199 [411] Train's auc: 0.917875 Evaluation's auc: 0.841874 [412] Train's auc: 0.917967 Evaluation's auc: 0.841902 [413] Train's auc: 0.918101 Evaluation's auc: 0.841877 [414] Train's auc: 0.918172 Evaluation's auc: 0.841886 [415] Train's auc: 0.918284 Evaluation's auc: 0.841861 [416] Train's auc: 0.918397 Evaluation's auc: 0.841829 [417] Train's auc: 0.918534 Evaluation's auc: 0.841831 [418] Train's auc: 0.918634 Evaluation's auc: 0.841853 [419] Train's auc: 0.918795 Evaluation's auc: 0.841811 [420] Train's auc: 0.918879 Evaluation's auc: 0.841773 [421] Train's auc: 0.918982 Evaluation's auc: 0.841729 [422] Train's auc: 0.919135 Evaluation's auc: 0.841724 [423] Train's auc: 0.919219 Evaluation's auc: 0.841733 [424] Train's auc: 0.919345 Evaluation's auc: 0.841704 [425] Train's auc: 0.919455 Evaluation's auc: 0.841704 [426] Train's auc: 0.919602 Evaluation's auc: 0.841627 [427] Train's auc: 0.919775 Evaluation's auc: 0.84162 [428] Train's auc: 0.919846 Evaluation's auc: 0.841611 [429] Train's auc: 0.919953 Evaluation's auc: 0.841559 [430] Train's auc: 0.92006 Evaluation's auc: 0.841562 [431] Train's auc: 0.920171 Evaluation's auc: 0.841593 [432] Train's auc: 0.920239 Evaluation's auc: 0.841598 [433] Train's auc: 0.920339 Evaluation's auc: 0.841598 [434] Train's auc: 0.920422 Evaluation's auc: 0.841619 [435] Train's auc: 0.920519 Evaluation's auc: 0.841629 [436] Train's auc: 0.920614 Evaluation's auc: 0.841614 [437] Train's auc: 0.920734 Evaluation's auc: 0.841582 [438] Train's auc: 0.920877 Evaluation's auc: 0.841575 [439] Train's auc: 0.920944 Evaluation's auc: 0.841552 [440] Train's auc: 0.921047 Evaluation's auc: 0.841478 [441] Train's auc: 0.92111 Evaluation's auc: 0.841504 [442] Train's auc: 0.921211 Evaluation's auc: 0.841521 [443] Train's auc: 0.921367 Evaluation's auc: 0.841477 [444] Train's auc: 0.92148 Evaluation's auc: 0.841488 [445] Train's auc: 0.92155 Evaluation's auc: 0.841482 [446] Train's auc: 0.921611 Evaluation's auc: 0.8415 [447] Train's auc: 0.921688 Evaluation's auc: 0.841515 [448] Train's auc: 0.921775 Evaluation's auc: 0.841533 [449] Train's auc: 0.921933 Evaluation's auc: 0.84148 [450] Train's auc: 0.92205 Evaluation's auc: 0.841497 [451] Train's auc: 0.922188 Evaluation's auc: 0.841465 [452] Train's auc: 0.922261 Evaluation's auc: 0.841467 [453] Train's auc: 0.922352 Evaluation's auc: 0.841457 [454] Train's auc: 0.922403 Evaluation's auc: 0.841457 [455] Train's auc: 0.922501 Evaluation's auc: 0.841399 [456] Train's auc: 0.922606 Evaluation's auc: 0.841412 [457] Train's auc: 0.922678 Evaluation's auc: 0.841403 [458] Train's auc: 0.922805 Evaluation's auc: 0.841373 [459] Train's auc: 0.922891 Evaluation's auc: 0.841355 [460] Train's auc: 0.923007 Evaluation's auc: 0.84127 [461] Train's auc: 0.92304 Evaluation's auc: 0.841273 [462] Train's auc: 0.923126 Evaluation's auc: 0.841471 [463] Train's auc: 0.92315 Evaluation's auc: 0.84149 [464] Train's auc: 0.923257 Evaluation's auc: 0.841456 [465] Train's auc: 0.923337 Evaluation's auc: 0.841439 [466] Train's auc: 0.923429 Evaluation's auc: 0.841389 [467] Train's auc: 0.92352 Evaluation's auc: 0.841453 [468] Train's auc: 0.923617 Evaluation's auc: 0.841457 [469] Train's auc: 0.923709 Evaluation's auc: 0.841459 [470] Train's auc: 0.92378 Evaluation's auc: 0.841411 [471] Train's auc: 0.92384 Evaluation's auc: 0.841415 [472] Train's auc: 0.923889 Evaluation's auc: 0.841402 [473] Train's auc: 0.924001 Evaluation's auc: 0.841417 [474] Train's auc: 0.924141 Evaluation's auc: 0.841384 [475] Train's auc: 0.924205 Evaluation's auc: 0.841392 [476] Train's auc: 0.924295 Evaluation's auc: 0.841454 [477] Train's auc: 0.924381 Evaluation's auc: 0.841409 [478] Train's auc: 0.924548 Evaluation's auc: 0.841447 [479] Train's auc: 0.924644 Evaluation's auc: 0.841414 [480] Train's auc: 0.924764 Evaluation's auc: 0.841452 [481] Train's auc: 0.924855 Evaluation's auc: 0.841468 [482] Train's auc: 0.924887 Evaluation's auc: 0.841453 [483] Train's auc: 0.924996 Evaluation's auc: 0.841471 [484] Train's auc: 0.925092 Evaluation's auc: 0.841484 [485] Train's auc: 0.92519 Evaluation's auc: 0.841479 [486] Train's auc: 0.925245 Evaluation's auc: 0.84146 [487] Train's auc: 0.925354 Evaluation's auc: 0.841476 [488] Train's auc: 0.925433 Evaluation's auc: 0.841491 [489] Train's auc: 0.92555 Evaluation's auc: 0.841581 [490] Train's auc: 0.925616 Evaluation's auc: 0.841592 [491] Train's auc: 0.925699 Evaluation's auc: 0.841561 [492] Train's auc: 0.925824 Evaluation's auc: 0.84156 [493] Train's auc: 0.92595 Evaluation's auc: 0.841482 [494] Train's auc: 0.926045 Evaluation's auc: 0.841477 [495] Train's auc: 0.92612 Evaluation's auc: 0.841462 [496] Train's auc: 0.926219 Evaluation's auc: 0.841478 [497] Train's auc: 0.926265 Evaluation's auc: 0.841466 [498] Train's auc: 0.926389 Evaluation's auc: 0.841497 [499] Train's auc: 0.926466 Evaluation's auc: 0.841515 [500] Train's auc: 0.926561 Evaluation's auc: 0.841514 [501] Train's auc: 0.926649 Evaluation's auc: 0.841518 [502] Train's auc: 0.926768 Evaluation's auc: 0.841507 [503] Train's auc: 0.926837 Evaluation's auc: 0.841545 [504] Train's auc: 0.926924 Evaluation's auc: 0.841616 [505] Train's auc: 0.927079 Evaluation's auc: 0.841758 [506] Train's auc: 0.927225 Evaluation's auc: 0.841727 [507] Train's auc: 0.927364 Evaluation's auc: 0.84163 [508] Train's auc: 0.927474 Evaluation's auc: 0.841619 [509] Train's auc: 0.927584 Evaluation's auc: 0.841552 [510] Train's auc: 0.927651 Evaluation's auc: 0.841576 [511] Train's auc: 0.927696 Evaluation's auc: 0.841534 [512] Train's auc: 0.927797 Evaluation's auc: 0.841556 [513] Train's auc: 0.927898 Evaluation's auc: 0.84158 [514] Train's auc: 0.927954 Evaluation's auc: 0.841697 [515] Train's auc: 0.928074 Evaluation's auc: 0.841683 [516] Train's auc: 0.928107 Evaluation's auc: 0.841681 [517] Train's auc: 0.928253 Evaluation's auc: 0.841672 [518] Train's auc: 0.928268 Evaluation's auc: 0.841645 [519] Train's auc: 0.928391 Evaluation's auc: 0.841625 [520] Train's auc: 0.928493 Evaluation's auc: 0.841615 [521] Train's auc: 0.928594 Evaluation's auc: 0.841595 [522] Train's auc: 0.928686 Evaluation's auc: 0.84158 [523] Train's auc: 0.928786 Evaluation's auc: 0.84163 [524] Train's auc: 0.928845 Evaluation's auc: 0.841621 [525] Train's auc: 0.928924 Evaluation's auc: 0.841577 [526] Train's auc: 0.92904 Evaluation's auc: 0.841534 [527] Train's auc: 0.929126 Evaluation's auc: 0.841697 [528] Train's auc: 0.929223 Evaluation's auc: 0.84165 [529] Train's auc: 0.929345 Evaluation's auc: 0.8416 [530] Train's auc: 0.929448 Evaluation's auc: 0.841575 [531] Train's auc: 0.929556 Evaluation's auc: 0.841568 [532] Train's auc: 0.929597 Evaluation's auc: 0.841559 [533] Train's auc: 0.929634 Evaluation's auc: 0.841562 [534] Train's auc: 0.929794 Evaluation's auc: 0.841514 [535] Train's auc: 0.929969 Evaluation's auc: 0.841411 [536] Train's auc: 0.930006 Evaluation's auc: 0.841411 [537] Train's auc: 0.930073 Evaluation's auc: 0.841421 [538] Train's auc: 0.930161 Evaluation's auc: 0.841349 [539] Train's auc: 0.930263 Evaluation's auc: 0.841339 [540] Train's auc: 0.930351 Evaluation's auc: 0.841301 [541] Train's auc: 0.930477 Evaluation's auc: 0.841226 [542] Train's auc: 0.930564 Evaluation's auc: 0.841213 [543] Train's auc: 0.930664 Evaluation's auc: 0.841134 [544] Train's auc: 0.930808 Evaluation's auc: 0.841104 [545] Train's auc: 0.930947 Evaluation's auc: 0.841099 [546] Train's auc: 0.931013 Evaluation's auc: 0.841085 [547] Train's auc: 0.931075 Evaluation's auc: 0.841099 [548] Train's auc: 0.931198 Evaluation's auc: 0.841174 [549] Train's auc: 0.931296 Evaluation's auc: 0.841203 [550] Train's auc: 0.931361 Evaluation's auc: 0.84124 [551] Train's auc: 0.931444 Evaluation's auc: 0.841211 [552] Train's auc: 0.93153 Evaluation's auc: 0.841187 [553] Train's auc: 0.931553 Evaluation's auc: 0.84116 [554] Train's auc: 0.931643 Evaluation's auc: 0.841177 [555] Train's auc: 0.931725 Evaluation's auc: 0.841139 [556] Train's auc: 0.931814 Evaluation's auc: 0.841149 [557] Train's auc: 0.931877 Evaluation's auc: 0.841135 [558] Train's auc: 0.931974 Evaluation's auc: 0.841088 [559] Train's auc: 0.932065 Evaluation's auc: 0.841078 [560] Train's auc: 0.932168 Evaluation's auc: 0.841073 [561] Train's auc: 0.932293 Evaluation's auc: 0.841065 [562] Train's auc: 0.932371 Evaluation's auc: 0.841063 [563] Train's auc: 0.932458 Evaluation's auc: 0.841016 [564] Train's auc: 0.932525 Evaluation's auc: 0.841224 [565] Train's auc: 0.932591 Evaluation's auc: 0.841247 [566] Train's auc: 0.932645 Evaluation's auc: 0.841281 [567] Train's auc: 0.932684 Evaluation's auc: 0.841273 [568] Train's auc: 0.932773 Evaluation's auc: 0.841279 [569] Train's auc: 0.932826 Evaluation's auc: 0.841236 [570] Train's auc: 0.932928 Evaluation's auc: 0.84124 [571] Train's auc: 0.93301 Evaluation's auc: 0.841243 [572] Train's auc: 0.933078 Evaluation's auc: 0.841327 [573] Train's auc: 0.933102 Evaluation's auc: 0.841325 [574] Train's auc: 0.933274 Evaluation's auc: 0.841428 [575] Train's auc: 0.933326 Evaluation's auc: 0.841372 [576] Train's auc: 0.933421 Evaluation's auc: 0.841371 [577] Train's auc: 0.933469 Evaluation's auc: 0.841346 [578] Train's auc: 0.933564 Evaluation's auc: 0.841416 [579] Train's auc: 0.933744 Evaluation's auc: 0.841419 [580] Train's auc: 0.933796 Evaluation's auc: 0.841426 [581] Train's auc: 0.933894 Evaluation's auc: 0.841451 [582] Train's auc: 0.933977 Evaluation's auc: 0.841407 [583] Train's auc: 0.934038 Evaluation's auc: 0.841401 [584] Train's auc: 0.934129 Evaluation's auc: 0.841464 [585] Train's auc: 0.934195 Evaluation's auc: 0.841461 [586] Train's auc: 0.934321 Evaluation's auc: 0.841491 [587] Train's auc: 0.934365 Evaluation's auc: 0.841473 [588] Train's auc: 0.934428 Evaluation's auc: 0.841454 [589] Train's auc: 0.93452 Evaluation's auc: 0.841433 [590] Train's auc: 0.934601 Evaluation's auc: 0.84142 [591] Train's auc: 0.934688 Evaluation's auc: 0.84139 [592] Train's auc: 0.93473 Evaluation's auc: 0.841374 [593] Train's auc: 0.93482 Evaluation's auc: 0.841366 [594] Train's auc: 0.9349 Evaluation's auc: 0.841343 [595] Train's auc: 0.934989 Evaluation's auc: 0.841317 [596] Train's auc: 0.93509 Evaluation's auc: 0.841308 [597] Train's auc: 0.935154 Evaluation's auc: 0.841339 [598] Train's auc: 0.935211 Evaluation's auc: 0.841312 [599] Train's auc: 0.935287 Evaluation's auc: 0.841304 [600] Train's auc: 0.935369 Evaluation's auc: 0.841305 [601] Train's auc: 0.935434 Evaluation's auc: 0.841296 [602] Train's auc: 0.935501 Evaluation's auc: 0.841328 [603] Train's auc: 0.935567 Evaluation's auc: 0.841307 [604] Train's auc: 0.935656 Evaluation's auc: 0.841309 [605] Train's auc: 0.935765 Evaluation's auc: 0.841315 [606] Train's auc: 0.935851 Evaluation's auc: 0.841337 [607] Train's auc: 0.935922 Evaluation's auc: 0.841344 [608] Train's auc: 0.936018 Evaluation's auc: 0.841317 [609] Train's auc: 0.936105 Evaluation's auc: 0.841298 [610] Train's auc: 0.936194 Evaluation's auc: 0.841365 [611] Train's auc: 0.936306 Evaluation's auc: 0.841339 [612] Train's auc: 0.936381 Evaluation's auc: 0.841398 [613] Train's auc: 0.936449 Evaluation's auc: 0.841351 [614] Train's auc: 0.936532 Evaluation's auc: 0.841335 [615] Train's auc: 0.936578 Evaluation's auc: 0.841307 [616] Train's auc: 0.936685 Evaluation's auc: 0.841271 [617] Train's auc: 0.93677 Evaluation's auc: 0.841268 [618] Train's auc: 0.936833 Evaluation's auc: 0.841272 [619] Train's auc: 0.936911 Evaluation's auc: 0.841239 [620] Train's auc: 0.936989 Evaluation's auc: 0.841181 [621] Train's auc: 0.93703 Evaluation's auc: 0.84116 [622] Train's auc: 0.937134 Evaluation's auc: 0.841178 [623] Train's auc: 0.937184 Evaluation's auc: 0.841152 [624] Train's auc: 0.93722 Evaluation's auc: 0.841147 [625] Train's auc: 0.937264 Evaluation's auc: 0.84115 [626] Train's auc: 0.937317 Evaluation's auc: 0.841103 [627] Train's auc: 0.93738 Evaluation's auc: 0.841199 [628] Train's auc: 0.937453 Evaluation's auc: 0.841148 [629] Train's auc: 0.937506 Evaluation's auc: 0.841116 [630] Train's auc: 0.937602 Evaluation's auc: 0.841101 [631] Train's auc: 0.937647 Evaluation's auc: 0.841084 [632] Train's auc: 0.937751 Evaluation's auc: 0.841104 [633] Train's auc: 0.937804 Evaluation's auc: 0.841111 [634] Train's auc: 0.937865 Evaluation's auc: 0.841122 [635] Train's auc: 0.937956 Evaluation's auc: 0.841131 [636] Train's auc: 0.938014 Evaluation's auc: 0.841102 [637] Train's auc: 0.938117 Evaluation's auc: 0.841043 [638] Train's auc: 0.938205 Evaluation's auc: 0.841023 [639] Train's auc: 0.93823 Evaluation's auc: 0.840975 [640] Train's auc: 0.938292 Evaluation's auc: 0.840951 [641] Train's auc: 0.938368 Evaluation's auc: 0.840931 [642] Train's auc: 0.93842 Evaluation's auc: 0.840921 [643] Train's auc: 0.938499 Evaluation's auc: 0.840929 [644] Train's auc: 0.938576 Evaluation's auc: 0.840931 [645] Train's auc: 0.938623 Evaluation's auc: 0.84099 [646] Train's auc: 0.938729 Evaluation's auc: 0.841 [647] Train's auc: 0.938781 Evaluation's auc: 0.841011 [648] Train's auc: 0.93883 Evaluation's auc: 0.840968 [649] Train's auc: 0.938918 Evaluation's auc: 0.84095 [650] Train's auc: 0.938988 Evaluation's auc: 0.840962 [651] Train's auc: 0.939082 Evaluation's auc: 0.840962 [652] Train's auc: 0.939201 Evaluation's auc: 0.840951 [653] Train's auc: 0.939287 Evaluation's auc: 0.840931 [654] Train's auc: 0.939355 Evaluation's auc: 0.840877 [655] Train's auc: 0.939441 Evaluation's auc: 0.840837 [656] Train's auc: 0.93952 Evaluation's auc: 0.840813 [657] Train's auc: 0.939574 Evaluation's auc: 0.840809 [658] Train's auc: 0.939676 Evaluation's auc: 0.840815 [659] Train's auc: 0.939724 Evaluation's auc: 0.840811 [660] Train's auc: 0.93981 Evaluation's auc: 0.840785 [661] Train's auc: 0.93988 Evaluation's auc: 0.840777 [662] Train's auc: 0.939947 Evaluation's auc: 0.84073 [663] Train's auc: 0.940038 Evaluation's auc: 0.840782 [664] Train's auc: 0.940072 Evaluation's auc: 0.840794 [665] Train's auc: 0.940104 Evaluation's auc: 0.840803 [666] Train's auc: 0.94021 Evaluation's auc: 0.84075 [667] Train's auc: 0.940247 Evaluation's auc: 0.840721 [668] Train's auc: 0.940332 Evaluation's auc: 0.840714 [669] Train's auc: 0.940345 Evaluation's auc: 0.840689 [670] Train's auc: 0.940403 Evaluation's auc: 0.840715 [671] Train's auc: 0.94045 Evaluation's auc: 0.840717 [672] Train's auc: 0.940509 Evaluation's auc: 0.840721 [673] Train's auc: 0.940617 Evaluation's auc: 0.840813 [674] Train's auc: 0.940639 Evaluation's auc: 0.840787 [675] Train's auc: 0.940768 Evaluation's auc: 0.840784 [676] Train's auc: 0.940842 Evaluation's auc: 0.840803 [677] Train's auc: 0.940899 Evaluation's auc: 0.840807 [678] Train's auc: 0.940972 Evaluation's auc: 0.840743 [679] Train's auc: 0.941057 Evaluation's auc: 0.840804 [680] Train's auc: 0.941119 Evaluation's auc: 0.840812 [681] Train's auc: 0.941195 Evaluation's auc: 0.840932 [682] Train's auc: 0.941293 Evaluation's auc: 0.840853 [683] Train's auc: 0.941363 Evaluation's auc: 0.840897 [684] Train's auc: 0.941432 Evaluation's auc: 0.840888 [685] Train's auc: 0.941463 Evaluation's auc: 0.840876 [686] Train's auc: 0.941479 Evaluation's auc: 0.840858 [687] Train's auc: 0.941559 Evaluation's auc: 0.840865 [688] Train's auc: 0.941593 Evaluation's auc: 0.840863 [689] Train's auc: 0.941667 Evaluation's auc: 0.84089 [690] Train's auc: 0.941752 Evaluation's auc: 0.840892 [691] Train's auc: 0.941833 Evaluation's auc: 0.840892 [692] Train's auc: 0.941891 Evaluation's auc: 0.840907 [693] Train's auc: 0.94195 Evaluation's auc: 0.840891 [694] Train's auc: 0.942001 Evaluation's auc: 0.8409 [695] Train's auc: 0.942077 Evaluation's auc: 0.840902 [696] Train's auc: 0.942121 Evaluation's auc: 0.840837 [697] Train's auc: 0.942158 Evaluation's auc: 0.840852 [698] Train's auc: 0.942254 Evaluation's auc: 0.840843 [699] Train's auc: 0.942297 Evaluation's auc: 0.840811 [700] Train's auc: 0.942375 Evaluation's auc: 0.84079 [701] Train's auc: 0.94246 Evaluation's auc: 0.840822 [702] Train's auc: 0.942539 Evaluation's auc: 0.840804 [703] Train's auc: 0.942629 Evaluation's auc: 0.840754 [704] Train's auc: 0.942719 Evaluation's auc: 0.840754 [705] Train's auc: 0.942815 Evaluation's auc: 0.840741 [706] Train's auc: 0.942904 Evaluation's auc: 0.84075 [707] Train's auc: 0.942982 Evaluation's auc: 0.840768 [708] Train's auc: 0.943043 Evaluation's auc: 0.840754 [709] Train's auc: 0.943076 Evaluation's auc: 0.840754 [710] Train's auc: 0.943176 Evaluation's auc: 0.840756 [711] Train's auc: 0.943226 Evaluation's auc: 0.840743 [712] Train's auc: 0.943333 Evaluation's auc: 0.840766 [713] Train's auc: 0.943382 Evaluation's auc: 0.840755 [714] Train's auc: 0.943454 Evaluation's auc: 0.840748 [715] Train's auc: 0.943552 Evaluation's auc: 0.84077 [716] Train's auc: 0.943595 Evaluation's auc: 0.840743 [717] Train's auc: 0.943607 Evaluation's auc: 0.840769 [718] Train's auc: 0.94367 Evaluation's auc: 0.840748 [719] Train's auc: 0.943748 Evaluation's auc: 0.840797 [720] Train's auc: 0.943823 Evaluation's auc: 0.840897 [721] Train's auc: 0.943931 Evaluation's auc: 0.840906 [722] Train's auc: 0.943973 Evaluation's auc: 0.840871 [723] Train's auc: 0.944063 Evaluation's auc: 0.840853 [724] Train's auc: 0.9441 Evaluation's auc: 0.840836 [725] Train's auc: 0.94418 Evaluation's auc: 0.840812 [726] Train's auc: 0.94424 Evaluation's auc: 0.840775 [727] Train's auc: 0.944286 Evaluation's auc: 0.840753 [728] Train's auc: 0.944362 Evaluation's auc: 0.840731 [729] Train's auc: 0.944374 Evaluation's auc: 0.840727 [730] Train's auc: 0.944427 Evaluation's auc: 0.840734 [731] Train's auc: 0.944453 Evaluation's auc: 0.840712 [732] Train's auc: 0.944498 Evaluation's auc: 0.84068 [733] Train's auc: 0.944577 Evaluation's auc: 0.840682 [734] Train's auc: 0.944671 Evaluation's auc: 0.8406 [735] Train's auc: 0.94472 Evaluation's auc: 0.840607 [736] Train's auc: 0.944735 Evaluation's auc: 0.840601 [737] Train's auc: 0.944799 Evaluation's auc: 0.840559 [738] Train's auc: 0.944899 Evaluation's auc: 0.840606 [739] Train's auc: 0.944953 Evaluation's auc: 0.840619 [740] Train's auc: 0.945029 Evaluation's auc: 0.840602 [741] Train's auc: 0.945101 Evaluation's auc: 0.840601 [742] Train's auc: 0.945171 Evaluation's auc: 0.840602 [743] Train's auc: 0.94525 Evaluation's auc: 0.840594 [744] Train's auc: 0.945294 Evaluation's auc: 0.840595 [745] Train's auc: 0.945307 Evaluation's auc: 0.840588 [746] Train's auc: 0.945396 Evaluation's auc: 0.840596 [747] Train's auc: 0.945405 Evaluation's auc: 0.840588 [748] Train's auc: 0.945454 Evaluation's auc: 0.840603 [749] Train's auc: 0.945464 Evaluation's auc: 0.840613 [750] Train's auc: 0.945506 Evaluation's auc: 0.840612 [751] Train's auc: 0.945554 Evaluation's auc: 0.840621 [752] Train's auc: 0.945606 Evaluation's auc: 0.840608 [753] Train's auc: 0.94566 Evaluation's auc: 0.840631 [754] Train's auc: 0.945728 Evaluation's auc: 0.840573 [755] Train's auc: 0.94579 Evaluation's auc: 0.840465 [756] Train's auc: 0.945857 Evaluation's auc: 0.840453 [757] Train's auc: 0.945898 Evaluation's auc: 0.840469 [758] Train's auc: 0.945944 Evaluation's auc: 0.84046 [759] Train's auc: 0.945962 Evaluation's auc: 0.840446 [760] Train's auc: 0.946022 Evaluation's auc: 0.840551 [761] Train's auc: 0.946092 Evaluation's auc: 0.840543 [762] Train's auc: 0.946213 Evaluation's auc: 0.84047 [763] Train's auc: 0.946288 Evaluation's auc: 0.840525 [764] Train's auc: 0.946321 Evaluation's auc: 0.840506 [765] Train's auc: 0.946384 Evaluation's auc: 0.840526 [766] Train's auc: 0.946462 Evaluation's auc: 0.840536 [767] Train's auc: 0.94651 Evaluation's auc: 0.840521 [768] Train's auc: 0.946542 Evaluation's auc: 0.840527 [769] Train's auc: 0.946616 Evaluation's auc: 0.840502 [770] Train's auc: 0.946628 Evaluation's auc: 0.840524 [771] Train's auc: 0.946683 Evaluation's auc: 0.840485 [772] Train's auc: 0.946759 Evaluation's auc: 0.840473 [773] Train's auc: 0.94682 Evaluation's auc: 0.840448 [774] Train's auc: 0.94684 Evaluation's auc: 0.840443 [775] Train's auc: 0.94693 Evaluation's auc: 0.840427 [776] Train's auc: 0.946987 Evaluation's auc: 0.840399 [777] Train's auc: 0.947054 Evaluation's auc: 0.840423 [778] Train's auc: 0.947106 Evaluation's auc: 0.840448 [779] Train's auc: 0.947176 Evaluation's auc: 0.840496 [780] Train's auc: 0.947258 Evaluation's auc: 0.840505 [781] Train's auc: 0.947289 Evaluation's auc: 0.840533 [782] Train's auc: 0.94736 Evaluation's auc: 0.84054 [783] Train's auc: 0.947432 Evaluation's auc: 0.840531 [784] Train's auc: 0.947471 Evaluation's auc: 0.840485 [785] Train's auc: 0.947557 Evaluation's auc: 0.84049 [786] Train's auc: 0.947612 Evaluation's auc: 0.840444 [787] Train's auc: 0.947687 Evaluation's auc: 0.840399 [788] Train's auc: 0.947754 Evaluation's auc: 0.840444 [789] Train's auc: 0.947793 Evaluation's auc: 0.8405 [790] Train's auc: 0.947829 Evaluation's auc: 0.840493 [791] Train's auc: 0.947919 Evaluation's auc: 0.840501 [792] Train's auc: 0.947965 Evaluation's auc: 0.840426 [793] Train's auc: 0.948054 Evaluation's auc: 0.840459 [794] Train's auc: 0.948113 Evaluation's auc: 0.840462 [795] Train's auc: 0.948175 Evaluation's auc: 0.840479 [796] Train's auc: 0.948219 Evaluation's auc: 0.840529 [797] Train's auc: 0.948269 Evaluation's auc: 0.840518 [798] Train's auc: 0.948311 Evaluation's auc: 0.840508 [799] Train's auc: 0.948358 Evaluation's auc: 0.840499 [800] Train's auc: 0.948463 Evaluation's auc: 0.840422 [801] Train's auc: 0.948511 Evaluation's auc: 0.840424 [802] Train's auc: 0.948571 Evaluation's auc: 0.840426 [803] Train's auc: 0.948622 Evaluation's auc: 0.84062 [804] Train's auc: 0.948702 Evaluation's auc: 0.840589 [805] Train's auc: 0.948736 Evaluation's auc: 0.840597 [806] Train's auc: 0.94883 Evaluation's auc: 0.840614 [807] Train's auc: 0.948887 Evaluation's auc: 0.840602 [808] Train's auc: 0.94895 Evaluation's auc: 0.840622 [809] Train's auc: 0.949014 Evaluation's auc: 0.84059 [810] Train's auc: 0.949101 Evaluation's auc: 0.840626 [811] Train's auc: 0.949144 Evaluation's auc: 0.84061 [812] Train's auc: 0.949199 Evaluation's auc: 0.840628 [813] Train's auc: 0.949233 Evaluation's auc: 0.840597 [814] Train's auc: 0.949263 Evaluation's auc: 0.84059 [815] Train's auc: 0.949303 Evaluation's auc: 0.840565 [816] Train's auc: 0.949356 Evaluation's auc: 0.8406 [817] Train's auc: 0.949417 Evaluation's auc: 0.840598 [818] Train's auc: 0.949502 Evaluation's auc: 0.840588 [819] Train's auc: 0.94958 Evaluation's auc: 0.840639 [820] Train's auc: 0.949613 Evaluation's auc: 0.840652 [821] Train's auc: 0.949663 Evaluation's auc: 0.840633 [822] Train's auc: 0.949718 Evaluation's auc: 0.840662 [823] Train's auc: 0.949761 Evaluation's auc: 0.840647 [824] Train's auc: 0.949831 Evaluation's auc: 0.840627 [825] Train's auc: 0.949894 Evaluation's auc: 0.8406 [826] Train's auc: 0.949957 Evaluation's auc: 0.840592 [827] Train's auc: 0.950032 Evaluation's auc: 0.840604 [828] Train's auc: 0.950086 Evaluation's auc: 0.840582 [829] Train's auc: 0.950118 Evaluation's auc: 0.840559 [830] Train's auc: 0.950148 Evaluation's auc: 0.84057 [831] Train's auc: 0.95021 Evaluation's auc: 0.840535 [832] Train's auc: 0.950205 Evaluation's auc: 0.840535 [833] Train's auc: 0.950225 Evaluation's auc: 0.840529 [834] Train's auc: 0.950282 Evaluation's auc: 0.840569 [835] Train's auc: 0.950313 Evaluation's auc: 0.840549 [836] Train's auc: 0.950373 Evaluation's auc: 0.84051 [837] Train's auc: 0.950428 Evaluation's auc: 0.840495 [838] Train's auc: 0.950456 Evaluation's auc: 0.840507 [839] Train's auc: 0.950532 Evaluation's auc: 0.840565 [840] Train's auc: 0.950583 Evaluation's auc: 0.840539 [841] Train's auc: 0.950623 Evaluation's auc: 0.840542 [842] Train's auc: 0.95066 Evaluation's auc: 0.840538 [843] Train's auc: 0.950705 Evaluation's auc: 0.840547 [844] Train's auc: 0.950731 Evaluation's auc: 0.840534 [845] Train's auc: 0.950788 Evaluation's auc: 0.840519 [846] Train's auc: 0.95084 Evaluation's auc: 0.840537 [847] Train's auc: 0.950903 Evaluation's auc: 0.840516 [848] Train's auc: 0.950959 Evaluation's auc: 0.840512 [849] Train's auc: 0.951023 Evaluation's auc: 0.840486 [850] Train's auc: 0.951117 Evaluation's auc: 0.840412 [851] Train's auc: 0.951165 Evaluation's auc: 0.84041 [852] Train's auc: 0.951218 Evaluation's auc: 0.840389 [853] Train's auc: 0.951246 Evaluation's auc: 0.840409 [854] Train's auc: 0.951297 Evaluation's auc: 0.840464 [855] Train's auc: 0.951372 Evaluation's auc: 0.840436 [856] Train's auc: 0.951407 Evaluation's auc: 0.84043 [857] Train's auc: 0.951477 Evaluation's auc: 0.840398 [858] Train's auc: 0.951515 Evaluation's auc: 0.84035 [859] Train's auc: 0.951579 Evaluation's auc: 0.840292 [860] Train's auc: 0.951661 Evaluation's auc: 0.840355 [861] Train's auc: 0.951712 Evaluation's auc: 0.840355 [862] Train's auc: 0.95176 Evaluation's auc: 0.840359 [863] Train's auc: 0.95184 Evaluation's auc: 0.840378 [864] Train's auc: 0.95188 Evaluation's auc: 0.840415 [865] Train's auc: 0.9519 Evaluation's auc: 0.840487 [866] Train's auc: 0.95194 Evaluation's auc: 0.840443 [867] Train's auc: 0.951981 Evaluation's auc: 0.840436 [868] Train's auc: 0.952012 Evaluation's auc: 0.840433 [869] Train's auc: 0.95202 Evaluation's auc: 0.840415 [870] Train's auc: 0.952088 Evaluation's auc: 0.840388 [871] Train's auc: 0.952148 Evaluation's auc: 0.840399 [872] Train's auc: 0.952212 Evaluation's auc: 0.840405 [873] Train's auc: 0.952246 Evaluation's auc: 0.840426 [874] Train's auc: 0.952295 Evaluation's auc: 0.840447 [875] Train's auc: 0.952362 Evaluation's auc: 0.840445 [876] Train's auc: 0.952402 Evaluation's auc: 0.840454 [877] Train's auc: 0.952469 Evaluation's auc: 0.840451 [878] Train's auc: 0.95252 Evaluation's auc: 0.840588 [879] Train's auc: 0.952575 Evaluation's auc: 0.840589 [880] Train's auc: 0.952606 Evaluation's auc: 0.84058 [881] Train's auc: 0.952636 Evaluation's auc: 0.840569 [882] Train's auc: 0.952657 Evaluation's auc: 0.84056 [883] Train's auc: 0.952716 Evaluation's auc: 0.840528 [884] Train's auc: 0.952778 Evaluation's auc: 0.840516 [885] Train's auc: 0.952851 Evaluation's auc: 0.840584 [886] Train's auc: 0.952921 Evaluation's auc: 0.840571 [887] Train's auc: 0.952932 Evaluation's auc: 0.840578 [888] Train's auc: 0.952972 Evaluation's auc: 0.840575 [889] Train's auc: 0.952991 Evaluation's auc: 0.840572 [890] Train's auc: 0.953058 Evaluation's auc: 0.84058 [891] Train's auc: 0.953136 Evaluation's auc: 0.840588 [892] Train's auc: 0.953168 Evaluation's auc: 0.840632 [893] Train's auc: 0.953222 Evaluation's auc: 0.840608 [894] Train's auc: 0.953255 Evaluation's auc: 0.84064 [895] Train's auc: 0.953289 Evaluation's auc: 0.840644 [896] Train's auc: 0.953324 Evaluation's auc: 0.840645 [897] Train's auc: 0.953365 Evaluation's auc: 0.840626 [898] Train's auc: 0.953407 Evaluation's auc: 0.840617 [899] Train's auc: 0.95345 Evaluation's auc: 0.840616 [900] Train's auc: 0.953476 Evaluation's auc: 0.840588 [901] Train's auc: 0.953555 Evaluation's auc: 0.840539 [902] Train's auc: 0.953608 Evaluation's auc: 0.840509 [903] Train's auc: 0.953655 Evaluation's auc: 0.84049 [904] Train's auc: 0.953666 Evaluation's auc: 0.840519 [905] Train's auc: 0.953725 Evaluation's auc: 0.840515 [906] Train's auc: 0.953763 Evaluation's auc: 0.840499 [907] Train's auc: 0.953814 Evaluation's auc: 0.840534 [908] Train's auc: 0.953886 Evaluation's auc: 0.840491 [909] Train's auc: 0.953931 Evaluation's auc: 0.840488 [910] Train's auc: 0.953956 Evaluation's auc: 0.840502 [911] Train's auc: 0.954004 Evaluation's auc: 0.840461 [912] Train's auc: 0.954058 Evaluation's auc: 0.840454 [913] Train's auc: 0.954088 Evaluation's auc: 0.840449 [914] Train's auc: 0.954142 Evaluation's auc: 0.840476 [915] Train's auc: 0.9542 Evaluation's auc: 0.840424 [916] Train's auc: 0.954267 Evaluation's auc: 0.840392 [917] Train's auc: 0.954315 Evaluation's auc: 0.840353 [918] Train's auc: 0.954318 Evaluation's auc: 0.840358 [919] Train's auc: 0.954383 Evaluation's auc: 0.840335 [920] Train's auc: 0.954427 Evaluation's auc: 0.840377 [921] Train's auc: 0.954492 Evaluation's auc: 0.840424 [922] Train's auc: 0.954535 Evaluation's auc: 0.840391 [923] Train's auc: 0.954621 Evaluation's auc: 0.840419 [924] Train's auc: 0.954694 Evaluation's auc: 0.840437 [925] Train's auc: 0.954744 Evaluation's auc: 0.840412 [926] Train's auc: 0.95479 Evaluation's auc: 0.840385 [927] Train's auc: 0.954908 Evaluation's auc: 0.840504 [928] Train's auc: 0.954948 Evaluation's auc: 0.840533 [929] Train's auc: 0.954997 Evaluation's auc: 0.840551 [930] Train's auc: 0.955047 Evaluation's auc: 0.840521 [931] Train's auc: 0.955095 Evaluation's auc: 0.840499 [932] Train's auc: 0.95515 Evaluation's auc: 0.840483 [933] Train's auc: 0.955208 Evaluation's auc: 0.84049 [934] Train's auc: 0.955256 Evaluation's auc: 0.84047 [935] Train's auc: 0.955259 Evaluation's auc: 0.840473 [936] Train's auc: 0.95532 Evaluation's auc: 0.840428 [937] Train's auc: 0.955364 Evaluation's auc: 0.840444 [938] Train's auc: 0.955383 Evaluation's auc: 0.840429 [939] Train's auc: 0.95543 Evaluation's auc: 0.840447 [940] Train's auc: 0.955465 Evaluation's auc: 0.840445 [941] Train's auc: 0.955497 Evaluation's auc: 0.840443 [942] Train's auc: 0.955546 Evaluation's auc: 0.840416 [943] Train's auc: 0.955574 Evaluation's auc: 0.840421 [944] Train's auc: 0.955606 Evaluation's auc: 0.840413 [945] Train's auc: 0.95566 Evaluation's auc: 0.840337 [946] Train's auc: 0.955689 Evaluation's auc: 0.840334 [947] Train's auc: 0.955736 Evaluation's auc: 0.840331 [948] Train's auc: 0.955803 Evaluation's auc: 0.840319 [949] Train's auc: 0.955849 Evaluation's auc: 0.840311 [950] Train's auc: 0.955889 Evaluation's auc: 0.840308 [951] Train's auc: 0.95592 Evaluation's auc: 0.840304 [952] Train's auc: 0.955938 Evaluation's auc: 0.840271 [953] Train's auc: 0.955976 Evaluation's auc: 0.840283 [954] Train's auc: 0.955981 Evaluation's auc: 0.840282 [955] Train's auc: 0.956003 Evaluation's auc: 0.840281 [956] Train's auc: 0.956015 Evaluation's auc: 0.840264 [957] Train's auc: 0.956052 Evaluation's auc: 0.840253 [958] Train's auc: 0.95609 Evaluation's auc: 0.840332 [959] Train's auc: 0.956136 Evaluation's auc: 0.840364 [960] Train's auc: 0.956149 Evaluation's auc: 0.84034 [961] Train's auc: 0.9562 Evaluation's auc: 0.840374 [962] Train's auc: 0.956252 Evaluation's auc: 0.840381 [963] Train's auc: 0.956271 Evaluation's auc: 0.840356 [964] Train's auc: 0.956335 Evaluation's auc: 0.840367 [965] Train's auc: 0.95637 Evaluation's auc: 0.840327 [966] Train's auc: 0.956428 Evaluation's auc: 0.840332 [967] Train's auc: 0.956455 Evaluation's auc: 0.840297 [968] Train's auc: 0.956479 Evaluation's auc: 0.84028 [969] Train's auc: 0.956526 Evaluation's auc: 0.84025 [970] Train's auc: 0.956539 Evaluation's auc: 0.840251 [971] Train's auc: 0.956592 Evaluation's auc: 0.840232 [972] Train's auc: 0.956659 Evaluation's auc: 0.840219 [973] Train's auc: 0.95668 Evaluation's auc: 0.840251 [974] Train's auc: 0.956718 Evaluation's auc: 0.840222 [975] Train's auc: 0.956773 Evaluation's auc: 0.840218 [976] Train's auc: 0.956812 Evaluation's auc: 0.840241 [977] Train's auc: 0.956862 Evaluation's auc: 0.840254 [978] Train's auc: 0.956938 Evaluation's auc: 0.840261 [979] Train's auc: 0.956959 Evaluation's auc: 0.840278 [980] Train's auc: 0.956976 Evaluation's auc: 0.840259 [981] Train's auc: 0.956983 Evaluation's auc: 0.840252 [982] Train's auc: 0.956994 Evaluation's auc: 0.840255 [983] Train's auc: 0.957004 Evaluation's auc: 0.840249 [984] Train's auc: 0.957051 Evaluation's auc: 0.840216 [985] Train's auc: 0.957114 Evaluation's auc: 0.840169 [986] Train's auc: 0.95715 Evaluation's auc: 0.840202 [987] Train's auc: 0.95716 Evaluation's auc: 0.840193 [988] Train's auc: 0.957183 Evaluation's auc: 0.840181 [989] Train's auc: 0.957223 Evaluation's auc: 0.840184 [990] Train's auc: 0.957273 Evaluation's auc: 0.840206 [991] Train's auc: 0.957355 Evaluation's auc: 0.840197 [992] Train's auc: 0.957411 Evaluation's auc: 0.840232 [993] Train's auc: 0.957453 Evaluation's auc: 0.840268 [994] Train's auc: 0.957487 Evaluation's auc: 0.840296 [995] Train's auc: 0.957542 Evaluation's auc: 0.840322 [996] Train's auc: 0.957579 Evaluation's auc: 0.840292 [997] Train's auc: 0.957641 Evaluation's auc: 0.840231 [998] Train's auc: 0.957677 Evaluation's auc: 0.840273 [999] Train's auc: 0.957706 Evaluation's auc: 0.840244 [1000] Train's auc: 0.957738 Evaluation's auc: 0.840284 [1001] Train's auc: 0.957756 Evaluation's auc: 0.840269 [1002] Train's auc: 0.957802 Evaluation's auc: 0.840252 [1003] Train's auc: 0.957836 Evaluation's auc: 0.840279 [1004] Train's auc: 0.957925 Evaluation's auc: 0.840349 [1005] Train's auc: 0.957987 Evaluation's auc: 0.840352 [1006] Train's auc: 0.958051 Evaluation's auc: 0.840349 [1007] Train's auc: 0.958096 Evaluation's auc: 0.840303 [1008] Train's auc: 0.958136 Evaluation's auc: 0.840284 [1009] Train's auc: 0.95821 Evaluation's auc: 0.840216 [1010] Train's auc: 0.958253 Evaluation's auc: 0.840188 [1011] Train's auc: 0.958307 Evaluation's auc: 0.840084 [1012] Train's auc: 0.958337 Evaluation's auc: 0.840085 [1013] Train's auc: 0.95841 Evaluation's auc: 0.840081 [1014] Train's auc: 0.958491 Evaluation's auc: 0.84007 [1015] Train's auc: 0.958546 Evaluation's auc: 0.840067 [1016] Train's auc: 0.958564 Evaluation's auc: 0.840044 [1017] Train's auc: 0.9586 Evaluation's auc: 0.840022 [1018] Train's auc: 0.958661 Evaluation's auc: 0.839979 [1019] Train's auc: 0.958708 Evaluation's auc: 0.839962 [1020] Train's auc: 0.958728 Evaluation's auc: 0.839957 [1021] Train's auc: 0.958757 Evaluation's auc: 0.839939 [1022] Train's auc: 0.958775 Evaluation's auc: 0.839923 [1023] Train's auc: 0.958833 Evaluation's auc: 0.839939 [1024] Train's auc: 0.958888 Evaluation's auc: 0.839936 [1025] Train's auc: 0.958917 Evaluation's auc: 0.839957 [1026] Train's auc: 0.958953 Evaluation's auc: 0.839974 [1027] Train's auc: 0.958994 Evaluation's auc: 0.839969 [1028] Train's auc: 0.95906 Evaluation's auc: 0.83993 [1029] Train's auc: 0.959108 Evaluation's auc: 0.840013 [1030] Train's auc: 0.95915 Evaluation's auc: 0.839995 [1031] Train's auc: 0.959204 Evaluation's auc: 0.839961 [1032] Train's auc: 0.959246 Evaluation's auc: 0.839962 [1033] Train's auc: 0.959271 Evaluation's auc: 0.839982 [1034] Train's auc: 0.95934 Evaluation's auc: 0.840012 [1035] Train's auc: 0.959385 Evaluation's auc: 0.840001 [1036] Train's auc: 0.959446 Evaluation's auc: 0.840059 [1037] Train's auc: 0.959487 Evaluation's auc: 0.840016 [1038] Train's auc: 0.959518 Evaluation's auc: 0.839993 [1039] Train's auc: 0.959571 Evaluation's auc: 0.83997 [1040] Train's auc: 0.959611 Evaluation's auc: 0.839937 [1041] Train's auc: 0.959653 Evaluation's auc: 0.839925 [1042] Train's auc: 0.959692 Evaluation's auc: 0.839922 [1043] Train's auc: 0.959697 Evaluation's auc: 0.839923 [1044] Train's auc: 0.959757 Evaluation's auc: 0.839912 [1045] Train's auc: 0.959804 Evaluation's auc: 0.839882 [1046] Train's auc: 0.959868 Evaluation's auc: 0.839897 [1047] Train's auc: 0.959913 Evaluation's auc: 0.839885 [1048] Train's auc: 0.959926 Evaluation's auc: 0.839869 [1049] Train's auc: 0.959962 Evaluation's auc: 0.839806 [1050] Train's auc: 0.959994 Evaluation's auc: 0.839825 [1051] Train's auc: 0.960019 Evaluation's auc: 0.839871 [1052] Train's auc: 0.960055 Evaluation's auc: 0.839826 [1053] Train's auc: 0.96013 Evaluation's auc: 0.839766 [1054] Train's auc: 0.960165 Evaluation's auc: 0.839867 [1055] Train's auc: 0.960185 Evaluation's auc: 0.839849 [1056] Train's auc: 0.960226 Evaluation's auc: 0.8398 [1057] Train's auc: 0.960258 Evaluation's auc: 0.839792 [1058] Train's auc: 0.960301 Evaluation's auc: 0.839769 [1059] Train's auc: 0.960343 Evaluation's auc: 0.839749 [1060] Train's auc: 0.960375 Evaluation's auc: 0.839727 [1061] Train's auc: 0.960411 Evaluation's auc: 0.839737 [1062] Train's auc: 0.960422 Evaluation's auc: 0.839723 [1063] Train's auc: 0.960463 Evaluation's auc: 0.839756 [1064] Train's auc: 0.960507 Evaluation's auc: 0.839725 [1065] Train's auc: 0.960534 Evaluation's auc: 0.83971 [1066] Train's auc: 0.960557 Evaluation's auc: 0.839702 [1067] Train's auc: 0.960606 Evaluation's auc: 0.839709 [1068] Train's auc: 0.960661 Evaluation's auc: 0.839663 [1069] Train's auc: 0.960695 Evaluation's auc: 0.839656 [1070] Train's auc: 0.960727 Evaluation's auc: 0.839635 [1071] Train's auc: 0.960748 Evaluation's auc: 0.839656 [1072] Train's auc: 0.960795 Evaluation's auc: 0.839636 [1073] Train's auc: 0.960804 Evaluation's auc: 0.839628 [1074] Train's auc: 0.960823 Evaluation's auc: 0.839646 [1075] Train's auc: 0.960831 Evaluation's auc: 0.839639 [1076] Train's auc: 0.960879 Evaluation's auc: 0.839666 [1077] Train's auc: 0.960939 Evaluation's auc: 0.839639 [1078] Train's auc: 0.960972 Evaluation's auc: 0.839632 [1079] Train's auc: 0.961056 Evaluation's auc: 0.839592 [1080] Train's auc: 0.961085 Evaluation's auc: 0.839588 [1081] Train's auc: 0.961113 Evaluation's auc: 0.83961 [1082] Train's auc: 0.961157 Evaluation's auc: 0.839571 [1083] Train's auc: 0.9612 Evaluation's auc: 0.839579 [1084] Train's auc: 0.961226 Evaluation's auc: 0.83953 [1085] Train's auc: 0.961265 Evaluation's auc: 0.839516 [1086] Train's auc: 0.961311 Evaluation's auc: 0.839531 [1087] Train's auc: 0.961329 Evaluation's auc: 0.839524 [1088] Train's auc: 0.961362 Evaluation's auc: 0.839525 [1089] Train's auc: 0.961397 Evaluation's auc: 0.839509 [1090] Train's auc: 0.96143 Evaluation's auc: 0.839467 [1091] Train's auc: 0.961464 Evaluation's auc: 0.839445 [1092] Train's auc: 0.961471 Evaluation's auc: 0.839437 [1093] Train's auc: 0.961527 Evaluation's auc: 0.839427 [1094] Train's auc: 0.961558 Evaluation's auc: 0.839457 [1095] Train's auc: 0.961606 Evaluation's auc: 0.839417 [1096] Train's auc: 0.96167 Evaluation's auc: 0.839361 [1097] Train's auc: 0.96172 Evaluation's auc: 0.839341 [1098] Train's auc: 0.96177 Evaluation's auc: 0.839343 [1099] Train's auc: 0.961799 Evaluation's auc: 0.839351 [1100] Train's auc: 0.961828 Evaluation's auc: 0.839328 [1101] Train's auc: 0.961866 Evaluation's auc: 0.839366 [1102] Train's auc: 0.961902 Evaluation's auc: 0.83934 [1103] Train's auc: 0.961932 Evaluation's auc: 0.839372 [1104] Train's auc: 0.961961 Evaluation's auc: 0.839362 [1105] Train's auc: 0.961989 Evaluation's auc: 0.839403 [1106] Train's auc: 0.962032 Evaluation's auc: 0.839372 [1107] Train's auc: 0.962074 Evaluation's auc: 0.839352 [1108] Train's auc: 0.962122 Evaluation's auc: 0.839312 [1109] Train's auc: 0.962159 Evaluation's auc: 0.83933 [1110] Train's auc: 0.962185 Evaluation's auc: 0.839316 [1111] Train's auc: 0.962231 Evaluation's auc: 0.839296 [1112] Train's auc: 0.962279 Evaluation's auc: 0.839316 [1113] Train's auc: 0.962317 Evaluation's auc: 0.839268 [1114] Train's auc: 0.962346 Evaluation's auc: 0.839271 [1115] Train's auc: 0.962389 Evaluation's auc: 0.839254 [1116] Train's auc: 0.962451 Evaluation's auc: 0.839226 [1117] Train's auc: 0.962492 Evaluation's auc: 0.83924 [1118] Train's auc: 0.962498 Evaluation's auc: 0.839243 [1119] Train's auc: 0.962541 Evaluation's auc: 0.839193 [1120] Train's auc: 0.962563 Evaluation's auc: 0.839205 [1121] Train's auc: 0.96258 Evaluation's auc: 0.839208 [1122] Train's auc: 0.96261 Evaluation's auc: 0.839202 [1123] Train's auc: 0.962631 Evaluation's auc: 0.839169 [1124] Train's auc: 0.962667 Evaluation's auc: 0.839157 [1125] Train's auc: 0.962676 Evaluation's auc: 0.839179 [1126] Train's auc: 0.962703 Evaluation's auc: 0.839189 [1127] Train's auc: 0.962737 Evaluation's auc: 0.839169 [1128] Train's auc: 0.962748 Evaluation's auc: 0.83916 [1129] Train's auc: 0.962756 Evaluation's auc: 0.839184 [1130] Train's auc: 0.962781 Evaluation's auc: 0.839159 [1131] Train's auc: 0.962831 Evaluation's auc: 0.839126 [1132] Train's auc: 0.962871 Evaluation's auc: 0.839117 [1133] Train's auc: 0.962883 Evaluation's auc: 0.839116 [1134] Train's auc: 0.96294 Evaluation's auc: 0.839114 [1135] Train's auc: 0.962954 Evaluation's auc: 0.839131 [1136] Train's auc: 0.962986 Evaluation's auc: 0.839099 [1137] Train's auc: 0.962993 Evaluation's auc: 0.839101 [1138] Train's auc: 0.963018 Evaluation's auc: 0.839156 [1139] Train's auc: 0.963064 Evaluation's auc: 0.839193 [1140] Train's auc: 0.963082 Evaluation's auc: 0.839192 [1141] Train's auc: 0.963098 Evaluation's auc: 0.839243 [1142] Train's auc: 0.96312 Evaluation's auc: 0.83922 [1143] Train's auc: 0.963132 Evaluation's auc: 0.839213 [1144] Train's auc: 0.963187 Evaluation's auc: 0.839198 [1145] Train's auc: 0.963207 Evaluation's auc: 0.83917 [1146] Train's auc: 0.963224 Evaluation's auc: 0.839165 [1147] Train's auc: 0.963232 Evaluation's auc: 0.839165 [1148] Train's auc: 0.96328 Evaluation's auc: 0.839138 [1149] Train's auc: 0.96334 Evaluation's auc: 0.839154 [1150] Train's auc: 0.963368 Evaluation's auc: 0.839139 [1151] Train's auc: 0.963399 Evaluation's auc: 0.839146 [1152] Train's auc: 0.963432 Evaluation's auc: 0.839114 [1153] Train's auc: 0.963466 Evaluation's auc: 0.83912 [1154] Train's auc: 0.963503 Evaluation's auc: 0.839087 [1155] Train's auc: 0.963514 Evaluation's auc: 0.839079 [1156] Train's auc: 0.963549 Evaluation's auc: 0.839052 [1157] Train's auc: 0.963599 Evaluation's auc: 0.839074 [1158] Train's auc: 0.963664 Evaluation's auc: 0.839037 [1159] Train's auc: 0.963674 Evaluation's auc: 0.839039 [1160] Train's auc: 0.963686 Evaluation's auc: 0.839057 [1161] Train's auc: 0.96374 Evaluation's auc: 0.839032 [1162] Train's auc: 0.963771 Evaluation's auc: 0.83901 [1163] Train's auc: 0.963796 Evaluation's auc: 0.839017 [1164] Train's auc: 0.963828 Evaluation's auc: 0.839028 [1165] Train's auc: 0.963845 Evaluation's auc: 0.83901 [1166] Train's auc: 0.963885 Evaluation's auc: 0.838997 [1167] Train's auc: 0.96391 Evaluation's auc: 0.83898 [1168] Train's auc: 0.963931 Evaluation's auc: 0.838973 [1169] Train's auc: 0.963976 Evaluation's auc: 0.83893 [1170] Train's auc: 0.963989 Evaluation's auc: 0.838908 [1171] Train's auc: 0.964001 Evaluation's auc: 0.83892 [1172] Train's auc: 0.964006 Evaluation's auc: 0.838943 [1173] Train's auc: 0.964042 Evaluation's auc: 0.838945 [1174] Train's auc: 0.964059 Evaluation's auc: 0.838964 [1175] Train's auc: 0.964058 Evaluation's auc: 0.838925 [1176] Train's auc: 0.964082 Evaluation's auc: 0.838944 [1177] Train's auc: 0.964119 Evaluation's auc: 0.838918 [1178] Train's auc: 0.964147 Evaluation's auc: 0.838966 [1179] Train's auc: 0.964198 Evaluation's auc: 0.838952 [1180] Train's auc: 0.96423 Evaluation's auc: 0.838967 [1181] Train's auc: 0.964248 Evaluation's auc: 0.83897 [1182] Train's auc: 0.964286 Evaluation's auc: 0.838943 [1183] Train's auc: 0.964314 Evaluation's auc: 0.838952 [1184] Train's auc: 0.964346 Evaluation's auc: 0.838931 [1185] Train's auc: 0.964365 Evaluation's auc: 0.838931 [1186] Train's auc: 0.964372 Evaluation's auc: 0.838918 [1187] Train's auc: 0.964393 Evaluation's auc: 0.838985 [1188] Train's auc: 0.964417 Evaluation's auc: 0.83898 [1189] Train's auc: 0.964485 Evaluation's auc: 0.838937 [1190] Train's auc: 0.964478 Evaluation's auc: 0.838943 [1191] Train's auc: 0.964531 Evaluation's auc: 0.838897 [1192] Train's auc: 0.964567 Evaluation's auc: 0.838895 [1193] Train's auc: 0.964595 Evaluation's auc: 0.838857 [1194] Train's auc: 0.964629 Evaluation's auc: 0.838844 [1195] Train's auc: 0.964676 Evaluation's auc: 0.838806 [1196] Train's auc: 0.964682 Evaluation's auc: 0.838786 [1197] Train's auc: 0.964721 Evaluation's auc: 0.838795 [1198] Train's auc: 0.964749 Evaluation's auc: 0.838813 [1199] Train's auc: 0.964774 Evaluation's auc: 0.838789 [1200] Train's auc: 0.964807 Evaluation's auc: 0.838792 [1201] Train's auc: 0.964842 Evaluation's auc: 0.838769 [1202] Train's auc: 0.964876 Evaluation's auc: 0.83874 [1203] Train's auc: 0.964933 Evaluation's auc: 0.838751 [1204] Train's auc: 0.964967 Evaluation's auc: 0.838764 [1205] Train's auc: 0.964999 Evaluation's auc: 0.838708 [1206] Train's auc: 0.965025 Evaluation's auc: 0.838721 [1207] Train's auc: 0.965069 Evaluation's auc: 0.838734 [1208] Train's auc: 0.965115 Evaluation's auc: 0.838716 [1209] Train's auc: 0.96512 Evaluation's auc: 0.838779 [1210] Train's auc: 0.96515 Evaluation's auc: 0.838747 [1211] Train's auc: 0.965157 Evaluation's auc: 0.838818 [1212] Train's auc: 0.965157 Evaluation's auc: 0.838816 [1213] Train's auc: 0.965201 Evaluation's auc: 0.838835 [1214] Train's auc: 0.965251 Evaluation's auc: 0.838843 [1215] Train's auc: 0.965308 Evaluation's auc: 0.838846 [1216] Train's auc: 0.965384 Evaluation's auc: 0.838833 [1217] Train's auc: 0.965427 Evaluation's auc: 0.838803 [1218] Train's auc: 0.965448 Evaluation's auc: 0.838795 [1219] Train's auc: 0.96547 Evaluation's auc: 0.83882 [1220] Train's auc: 0.965517 Evaluation's auc: 0.83881 [1221] Train's auc: 0.965563 Evaluation's auc: 0.838841 [1222] Train's auc: 0.965603 Evaluation's auc: 0.838856 [1223] Train's auc: 0.965641 Evaluation's auc: 0.838857 [1224] Train's auc: 0.965691 Evaluation's auc: 0.838864 [1225] Train's auc: 0.965702 Evaluation's auc: 0.838853 [1226] Train's auc: 0.965741 Evaluation's auc: 0.838809 [1227] Train's auc: 0.965775 Evaluation's auc: 0.838759 [1228] Train's auc: 0.965795 Evaluation's auc: 0.838738 [1229] Train's auc: 0.965835 Evaluation's auc: 0.838671 [1230] Train's auc: 0.965866 Evaluation's auc: 0.838684 [1231] Train's auc: 0.965884 Evaluation's auc: 0.838695 [1232] Train's auc: 0.9659 Evaluation's auc: 0.838681 [1233] Train's auc: 0.96595 Evaluation's auc: 0.838667 [1234] Train's auc: 0.965975 Evaluation's auc: 0.838657 [1235] Train's auc: 0.965994 Evaluation's auc: 0.838659 [1236] Train's auc: 0.966013 Evaluation's auc: 0.838659 [1237] Train's auc: 0.96605 Evaluation's auc: 0.838621 [1238] Train's auc: 0.966076 Evaluation's auc: 0.838606 [1239] Train's auc: 0.966119 Evaluation's auc: 0.838641 [1240] Train's auc: 0.966168 Evaluation's auc: 0.838622 [1241] Train's auc: 0.966201 Evaluation's auc: 0.838648 [1242] Train's auc: 0.966213 Evaluation's auc: 0.838644 [1243] Train's auc: 0.966244 Evaluation's auc: 0.838658 [1244] Train's auc: 0.966277 Evaluation's auc: 0.838683 [1245] Train's auc: 0.96632 Evaluation's auc: 0.838702 [1246] Train's auc: 0.966336 Evaluation's auc: 0.838662 [1247] Train's auc: 0.966366 Evaluation's auc: 0.838662 [1248] Train's auc: 0.966412 Evaluation's auc: 0.838669 [1249] Train's auc: 0.966463 Evaluation's auc: 0.838649 [1250] Train's auc: 0.966481 Evaluation's auc: 0.838621 [1251] Train's auc: 0.966515 Evaluation's auc: 0.838615 [1252] Train's auc: 0.96655 Evaluation's auc: 0.838599 [1253] Train's auc: 0.966581 Evaluation's auc: 0.838618 [1254] Train's auc: 0.966616 Evaluation's auc: 0.838614 [1255] Train's auc: 0.966634 Evaluation's auc: 0.838631 [1256] Train's auc: 0.966641 Evaluation's auc: 0.838635 [1257] Train's auc: 0.966665 Evaluation's auc: 0.838627 [1258] Train's auc: 0.9667 Evaluation's auc: 0.838638 [1259] Train's auc: 0.966742 Evaluation's auc: 0.838651 [1260] Train's auc: 0.966763 Evaluation's auc: 0.838628 [1261] Train's auc: 0.96679 Evaluation's auc: 0.838598 [1262] Train's auc: 0.966802 Evaluation's auc: 0.838589 [1263] Train's auc: 0.96686 Evaluation's auc: 0.83857 [1264] Train's auc: 0.9669 Evaluation's auc: 0.838521 [1265] Train's auc: 0.966936 Evaluation's auc: 0.838538 [1266] Train's auc: 0.966979 Evaluation's auc: 0.838471 [1267] Train's auc: 0.967 Evaluation's auc: 0.83845 [1268] Train's auc: 0.967014 Evaluation's auc: 0.838477 [1269] Train's auc: 0.967042 Evaluation's auc: 0.838511 [1270] Train's auc: 0.967073 Evaluation's auc: 0.838526 [1271] Train's auc: 0.967084 Evaluation's auc: 0.838527 [1272] Train's auc: 0.967137 Evaluation's auc: 0.838488 [1273] Train's auc: 0.96714 Evaluation's auc: 0.838501 [1274] Train's auc: 0.967165 Evaluation's auc: 0.838512 [1275] Train's auc: 0.967226 Evaluation's auc: 0.838512 [1276] Train's auc: 0.967256 Evaluation's auc: 0.83855 [1277] Train's auc: 0.967271 Evaluation's auc: 0.838545 [1278] Train's auc: 0.967293 Evaluation's auc: 0.838519 [1279] Train's auc: 0.967326 Evaluation's auc: 0.838521 [1280] Train's auc: 0.967343 Evaluation's auc: 0.838492 [1281] Train's auc: 0.967357 Evaluation's auc: 0.838482 [1282] Train's auc: 0.967397 Evaluation's auc: 0.838455 [1283] Train's auc: 0.967441 Evaluation's auc: 0.838453 [1284] Train's auc: 0.967447 Evaluation's auc: 0.838453 [1285] Train's auc: 0.967514 Evaluation's auc: 0.838457 [1286] Train's auc: 0.967559 Evaluation's auc: 0.838496 [1287] Train's auc: 0.967585 Evaluation's auc: 0.838473 [1288] Train's auc: 0.967607 Evaluation's auc: 0.838458 [1289] Train's auc: 0.967677 Evaluation's auc: 0.838493 [1290] Train's auc: 0.967716 Evaluation's auc: 0.838474 [1291] Train's auc: 0.967752 Evaluation's auc: 0.838469 [1292] Train's auc: 0.967786 Evaluation's auc: 0.83846 [1293] Train's auc: 0.967801 Evaluation's auc: 0.838515 [1294] Train's auc: 0.967826 Evaluation's auc: 0.838543 [1295] Train's auc: 0.967864 Evaluation's auc: 0.838524 [1296] Train's auc: 0.967887 Evaluation's auc: 0.838513 [1297] Train's auc: 0.967911 Evaluation's auc: 0.838554 [1298] Train's auc: 0.967924 Evaluation's auc: 0.838573 [1299] Train's auc: 0.967961 Evaluation's auc: 0.838598 [1300] Train's auc: 0.967984 Evaluation's auc: 0.838561 [1301] Train's auc: 0.968005 Evaluation's auc: 0.838554 [1302] Train's auc: 0.968015 Evaluation's auc: 0.838518 [1303] Train's auc: 0.96804 Evaluation's auc: 0.838485 [1304] Train's auc: 0.96807 Evaluation's auc: 0.83844 [1305] Train's auc: 0.968072 Evaluation's auc: 0.838439 [1306] Train's auc: 0.968094 Evaluation's auc: 0.838375 [1307] Train's auc: 0.96812 Evaluation's auc: 0.838357 [1308] Train's auc: 0.968143 Evaluation's auc: 0.838359 [1309] Train's auc: 0.968196 Evaluation's auc: 0.838322 [1310] Train's auc: 0.968231 Evaluation's auc: 0.838359 [1311] Train's auc: 0.968277 Evaluation's auc: 0.838334 [1312] Train's auc: 0.968321 Evaluation's auc: 0.838275 [1313] Train's auc: 0.968338 Evaluation's auc: 0.838268 [1314] Train's auc: 0.968371 Evaluation's auc: 0.838327 [1315] Train's auc: 0.968406 Evaluation's auc: 0.838352 [1316] Train's auc: 0.968434 Evaluation's auc: 0.838393 [1317] Train's auc: 0.968456 Evaluation's auc: 0.838358 [1318] Train's auc: 0.968488 Evaluation's auc: 0.838326 [1319] Train's auc: 0.968503 Evaluation's auc: 0.838308 [1320] Train's auc: 0.96851 Evaluation's auc: 0.838303 [1321] Train's auc: 0.968535 Evaluation's auc: 0.838333 [1322] Train's auc: 0.968548 Evaluation's auc: 0.83831 [1323] Train's auc: 0.968583 Evaluation's auc: 0.838295 [1324] Train's auc: 0.968603 Evaluation's auc: 0.83837 [1325] Train's auc: 0.968652 Evaluation's auc: 0.838352 [1326] Train's auc: 0.968669 Evaluation's auc: 0.838359 [1327] Train's auc: 0.968689 Evaluation's auc: 0.838352 [1328] Train's auc: 0.968721 Evaluation's auc: 0.838344 [1329] Train's auc: 0.968744 Evaluation's auc: 0.838312 [1330] Train's auc: 0.968764 Evaluation's auc: 0.838346 [1331] Train's auc: 0.968782 Evaluation's auc: 0.838346 [1332] Train's auc: 0.968789 Evaluation's auc: 0.838352 [1333] Train's auc: 0.96882 Evaluation's auc: 0.838347 [1334] Train's auc: 0.968843 Evaluation's auc: 0.838391 [1335] Train's auc: 0.968873 Evaluation's auc: 0.838355 [1336] Train's auc: 0.96892 Evaluation's auc: 0.838334 [1337] Train's auc: 0.96893 Evaluation's auc: 0.838335 [1338] Train's auc: 0.968976 Evaluation's auc: 0.838339 [1339] Train's auc: 0.968995 Evaluation's auc: 0.838355 [1340] Train's auc: 0.969036 Evaluation's auc: 0.838355 [1341] Train's auc: 0.969065 Evaluation's auc: 0.838352 [1342] Train's auc: 0.969107 Evaluation's auc: 0.83836 [1343] Train's auc: 0.969113 Evaluation's auc: 0.838353 [1344] Train's auc: 0.969136 Evaluation's auc: 0.838365 [1345] Train's auc: 0.969178 Evaluation's auc: 0.838398 [1346] Train's auc: 0.96919 Evaluation's auc: 0.838408 [1347] Train's auc: 0.969218 Evaluation's auc: 0.838376 [1348] Train's auc: 0.969244 Evaluation's auc: 0.838368 [1349] Train's auc: 0.969272 Evaluation's auc: 0.838338 [1350] Train's auc: 0.969315 Evaluation's auc: 0.838324 [1351] Train's auc: 0.969327 Evaluation's auc: 0.838312 [1352] Train's auc: 0.969347 Evaluation's auc: 0.838296 [1353] Train's auc: 0.969358 Evaluation's auc: 0.838296 [1354] Train's auc: 0.969368 Evaluation's auc: 0.838306 [1355] Train's auc: 0.969376 Evaluation's auc: 0.838302 [1356] Train's auc: 0.969404 Evaluation's auc: 0.838306 [1357] Train's auc: 0.969433 Evaluation's auc: 0.838314 [1358] Train's auc: 0.969432 Evaluation's auc: 0.838333 [1359] Train's auc: 0.969477 Evaluation's auc: 0.838342 [1360] Train's auc: 0.969511 Evaluation's auc: 0.838317 [1361] Train's auc: 0.969553 Evaluation's auc: 0.838455 [1362] Train's auc: 0.969558 Evaluation's auc: 0.838481 [1363] Train's auc: 0.969582 Evaluation's auc: 0.838478 [1364] Train's auc: 0.969596 Evaluation's auc: 0.838479 [1365] Train's auc: 0.969621 Evaluation's auc: 0.838464 [1366] Train's auc: 0.969645 Evaluation's auc: 0.838424 [1367] Train's auc: 0.969671 Evaluation's auc: 0.838419 [1368] Train's auc: 0.969676 Evaluation's auc: 0.838419 [1369] Train's auc: 0.969712 Evaluation's auc: 0.838424 [1370] Train's auc: 0.969745 Evaluation's auc: 0.838432 [1371] Train's auc: 0.969765 Evaluation's auc: 0.838396 [1372] Train's auc: 0.969798 Evaluation's auc: 0.838353 [1373] Train's auc: 0.969843 Evaluation's auc: 0.838327 [1374] Train's auc: 0.969869 Evaluation's auc: 0.838328 [1375] Train's auc: 0.969874 Evaluation's auc: 0.838318 [1376] Train's auc: 0.969894 Evaluation's auc: 0.838332 [1377] Train's auc: 0.969919 Evaluation's auc: 0.83832 [1378] Train's auc: 0.969948 Evaluation's auc: 0.838287 [1379] Train's auc: 0.969949 Evaluation's auc: 0.838287 [1380] Train's auc: 0.969983 Evaluation's auc: 0.838308 [1381] Train's auc: 0.97001 Evaluation's auc: 0.838321 [1382] Train's auc: 0.970051 Evaluation's auc: 0.838308 [1383] Train's auc: 0.970058 Evaluation's auc: 0.838319 [1384] Train's auc: 0.970061 Evaluation's auc: 0.838324 [1385] Train's auc: 0.970075 Evaluation's auc: 0.838328 [1386] Train's auc: 0.970105 Evaluation's auc: 0.838368 [1387] Train's auc: 0.970121 Evaluation's auc: 0.838364 [1388] Train's auc: 0.970129 Evaluation's auc: 0.838366 [1389] Train's auc: 0.970159 Evaluation's auc: 0.838375 [1390] Train's auc: 0.970175 Evaluation's auc: 0.838384 [1391] Train's auc: 0.97019 Evaluation's auc: 0.838408 [1392] Train's auc: 0.970209 Evaluation's auc: 0.838403 [1393] Train's auc: 0.970243 Evaluation's auc: 0.838416 [1394] Train's auc: 0.970279 Evaluation's auc: 0.838385 [1395] Train's auc: 0.970302 Evaluation's auc: 0.838383 [1396] Train's auc: 0.970316 Evaluation's auc: 0.838459 [1397] Train's auc: 0.970336 Evaluation's auc: 0.838442 [1398] Train's auc: 0.970394 Evaluation's auc: 0.838383 [1399] Train's auc: 0.97043 Evaluation's auc: 0.838369 [1400] Train's auc: 0.970436 Evaluation's auc: 0.838372 [1401] Train's auc: 0.970442 Evaluation's auc: 0.838366 [1402] Train's auc: 0.970455 Evaluation's auc: 0.838375 [1403] Train's auc: 0.970471 Evaluation's auc: 0.838372 [1404] Train's auc: 0.970479 Evaluation's auc: 0.838362 [1405] Train's auc: 0.970513 Evaluation's auc: 0.838356 [1406] Train's auc: 0.970512 Evaluation's auc: 0.838363 [1407] Train's auc: 0.97055 Evaluation's auc: 0.838337 [1408] Train's auc: 0.970587 Evaluation's auc: 0.838338 [1409] Train's auc: 0.970612 Evaluation's auc: 0.838287 [1410] Train's auc: 0.970653 Evaluation's auc: 0.838231 [1411] Train's auc: 0.970675 Evaluation's auc: 0.838223 [1412] Train's auc: 0.970686 Evaluation's auc: 0.838199 [1413] Train's auc: 0.970727 Evaluation's auc: 0.838207 [1414] Train's auc: 0.97075 Evaluation's auc: 0.838269 [1415] Train's auc: 0.970758 Evaluation's auc: 0.838271 [1416] Train's auc: 0.970791 Evaluation's auc: 0.838256 [1417] Train's auc: 0.970792 Evaluation's auc: 0.838247 [1418] Train's auc: 0.970826 Evaluation's auc: 0.838257 [1419] Train's auc: 0.970831 Evaluation's auc: 0.838253 [1420] Train's auc: 0.970849 Evaluation's auc: 0.838212 [1421] Train's auc: 0.970884 Evaluation's auc: 0.838213 [1422] Train's auc: 0.970905 Evaluation's auc: 0.838174 [1423] Train's auc: 0.970922 Evaluation's auc: 0.838182 [1424] Train's auc: 0.970933 Evaluation's auc: 0.83817 [1425] Train's auc: 0.97097 Evaluation's auc: 0.838223 [1426] Train's auc: 0.970976 Evaluation's auc: 0.838233 [1427] Train's auc: 0.971001 Evaluation's auc: 0.838241 [1428] Train's auc: 0.971039 Evaluation's auc: 0.838258 [1429] Train's auc: 0.971041 Evaluation's auc: 0.838264 [1430] Train's auc: 0.97106 Evaluation's auc: 0.838262 [1431] Train's auc: 0.971092 Evaluation's auc: 0.838265 [1432] Train's auc: 0.971114 Evaluation's auc: 0.838228 [1433] Train's auc: 0.971136 Evaluation's auc: 0.838222 [1434] Train's auc: 0.971168 Evaluation's auc: 0.838219 [1435] Train's auc: 0.971188 Evaluation's auc: 0.838182 [1436] Train's auc: 0.971204 Evaluation's auc: 0.838255 [1437] Train's auc: 0.971223 Evaluation's auc: 0.838243 [1438] Train's auc: 0.971226 Evaluation's auc: 0.838264 [1439] Train's auc: 0.971245 Evaluation's auc: 0.838229 [1440] Train's auc: 0.971274 Evaluation's auc: 0.8382 [1441] Train's auc: 0.971292 Evaluation's auc: 0.838227 [1442] Train's auc: 0.971304 Evaluation's auc: 0.838211 [1443] Train's auc: 0.971309 Evaluation's auc: 0.838228 [1444] Train's auc: 0.971323 Evaluation's auc: 0.838229 [1445] Train's auc: 0.971339 Evaluation's auc: 0.838201 [1446] Train's auc: 0.97137 Evaluation's auc: 0.838199 [1447] Train's auc: 0.971389 Evaluation's auc: 0.838207 [1448] Train's auc: 0.971422 Evaluation's auc: 0.838194 [1449] Train's auc: 0.971471 Evaluation's auc: 0.838197 [1450] Train's auc: 0.971502 Evaluation's auc: 0.838186 [1451] Train's auc: 0.971523 Evaluation's auc: 0.838171 [1452] Train's auc: 0.971546 Evaluation's auc: 0.8382 [1453] Train's auc: 0.971551 Evaluation's auc: 0.838186 [1454] Train's auc: 0.971578 Evaluation's auc: 0.838191 [1455] Train's auc: 0.971617 Evaluation's auc: 0.83818 [1456] Train's auc: 0.971634 Evaluation's auc: 0.838147 [1457] Train's auc: 0.971668 Evaluation's auc: 0.838158 [1458] Train's auc: 0.971682 Evaluation's auc: 0.838179 [1459] Train's auc: 0.97172 Evaluation's auc: 0.838178 [1460] Train's auc: 0.971752 Evaluation's auc: 0.838171 [1461] Train's auc: 0.971786 Evaluation's auc: 0.838141 [1462] Train's auc: 0.971789 Evaluation's auc: 0.83813 [1463] Train's auc: 0.971821 Evaluation's auc: 0.838089 [1464] Train's auc: 0.97185 Evaluation's auc: 0.83814 [1465] Train's auc: 0.971845 Evaluation's auc: 0.838135 [1466] Train's auc: 0.971864 Evaluation's auc: 0.838124 [1467] Train's auc: 0.971892 Evaluation's auc: 0.838113 [1468] Train's auc: 0.971932 Evaluation's auc: 0.838119 [1469] Train's auc: 0.971953 Evaluation's auc: 0.838087 [1470] Train's auc: 0.971969 Evaluation's auc: 0.83807 [1471] Train's auc: 0.971983 Evaluation's auc: 0.838108 [1472] Train's auc: 0.972017 Evaluation's auc: 0.838126 [1473] Train's auc: 0.97205 Evaluation's auc: 0.838131 [1474] Train's auc: 0.972052 Evaluation's auc: 0.838132 [1475] Train's auc: 0.972073 Evaluation's auc: 0.838156 [1476] Train's auc: 0.972093 Evaluation's auc: 0.838125 [1477] Train's auc: 0.972099 Evaluation's auc: 0.838112 [1478] Train's auc: 0.97211 Evaluation's auc: 0.838092 [1479] Train's auc: 0.972125 Evaluation's auc: 0.838091 [1480] Train's auc: 0.972145 Evaluation's auc: 0.838042 [1481] Train's auc: 0.972175 Evaluation's auc: 0.83805 [1482] Train's auc: 0.972196 Evaluation's auc: 0.838059 [1483] Train's auc: 0.972199 Evaluation's auc: 0.838054 [1484] Train's auc: 0.97222 Evaluation's auc: 0.83806 [1485] Train's auc: 0.972292 Evaluation's auc: 0.838085 [1486] Train's auc: 0.972299 Evaluation's auc: 0.838046 [1487] Train's auc: 0.972329 Evaluation's auc: 0.838049 [1488] Train's auc: 0.97234 Evaluation's auc: 0.838022 [1489] Train's auc: 0.972367 Evaluation's auc: 0.838005 [1490] Train's auc: 0.972369 Evaluation's auc: 0.838041 [1491] Train's auc: 0.972397 Evaluation's auc: 0.838005 [1492] Train's auc: 0.972424 Evaluation's auc: 0.838014 [1493] Train's auc: 0.972467 Evaluation's auc: 0.838004 [1494] Train's auc: 0.972494 Evaluation's auc: 0.838054 [1495] Train's auc: 0.972508 Evaluation's auc: 0.838066 [1496] Train's auc: 0.972534 Evaluation's auc: 0.838056 [1497] Train's auc: 0.972559 Evaluation's auc: 0.83804 [1498] Train's auc: 0.972601 Evaluation's auc: 0.837977 [1499] Train's auc: 0.97263 Evaluation's auc: 0.837954 [1500] Train's auc: 0.972647 Evaluation's auc: 0.837924 [1501] Train's auc: 0.972659 Evaluation's auc: 0.837969 [1502] Train's auc: 0.972679 Evaluation's auc: 0.837917 [1503] Train's auc: 0.972705 Evaluation's auc: 0.837973 [1504] Train's auc: 0.972739 Evaluation's auc: 0.837959 [1505] Train's auc: 0.97275 Evaluation's auc: 0.837958 [1506] Train's auc: 0.97276 Evaluation's auc: 0.837966 [1507] Train's auc: 0.972787 Evaluation's auc: 0.837958 [1508] Train's auc: 0.972813 Evaluation's auc: 0.837921 [1509] Train's auc: 0.972839 Evaluation's auc: 0.837868 [1510] Train's auc: 0.97285 Evaluation's auc: 0.837883 [1511] Train's auc: 0.972874 Evaluation's auc: 0.837836 [1512] Train's auc: 0.9729 Evaluation's auc: 0.837844 [1513] Train's auc: 0.972921 Evaluation's auc: 0.837801 [1514] Train's auc: 0.972923 Evaluation's auc: 0.837805 [1515] Train's auc: 0.972953 Evaluation's auc: 0.837777 [1516] Train's auc: 0.972961 Evaluation's auc: 0.837771 [1517] Train's auc: 0.973005 Evaluation's auc: 0.837743 [1518] Train's auc: 0.973026 Evaluation's auc: 0.837743 [1519] Train's auc: 0.973027 Evaluation's auc: 0.83777 [1520] Train's auc: 0.97305 Evaluation's auc: 0.837767 [1521] Train's auc: 0.973072 Evaluation's auc: 0.837764 [1522] Train's auc: 0.973087 Evaluation's auc: 0.837734 [1523] Train's auc: 0.973111 Evaluation's auc: 0.837697 [1524] Train's auc: 0.973117 Evaluation's auc: 0.837679 [1525] Train's auc: 0.973151 Evaluation's auc: 0.837674 [1526] Train's auc: 0.97318 Evaluation's auc: 0.837661 [1527] Train's auc: 0.973194 Evaluation's auc: 0.837618 [1528] Train's auc: 0.973205 Evaluation's auc: 0.837607 [1529] Train's auc: 0.973221 Evaluation's auc: 0.837596 [1530] Train's auc: 0.973247 Evaluation's auc: 0.837617 [1531] Train's auc: 0.973256 Evaluation's auc: 0.837645 [1532] Train's auc: 0.973268 Evaluation's auc: 0.837634 [1533] Train's auc: 0.973298 Evaluation's auc: 0.837617 [1534] Train's auc: 0.97332 Evaluation's auc: 0.837613 [1535] Train's auc: 0.973324 Evaluation's auc: 0.837626 [1536] Train's auc: 0.973341 Evaluation's auc: 0.837603 [1537] Train's auc: 0.973388 Evaluation's auc: 0.837692 [1538] Train's auc: 0.973404 Evaluation's auc: 0.837685 [1539] Train's auc: 0.973434 Evaluation's auc: 0.837673 [1540] Train's auc: 0.973446 Evaluation's auc: 0.837674 [1541] Train's auc: 0.973459 Evaluation's auc: 0.837657 [1542] Train's auc: 0.973473 Evaluation's auc: 0.837674 [1543] Train's auc: 0.973494 Evaluation's auc: 0.837663 [1544] Train's auc: 0.973499 Evaluation's auc: 0.837666 [1545] Train's auc: 0.973525 Evaluation's auc: 0.837664 [1546] Train's auc: 0.973537 Evaluation's auc: 0.837662 [1547] Train's auc: 0.973553 Evaluation's auc: 0.837619 [1548] Train's auc: 0.973568 Evaluation's auc: 0.837619 [1549] Train's auc: 0.973586 Evaluation's auc: 0.837628 [1550] Train's auc: 0.973603 Evaluation's auc: 0.837619 [1551] Train's auc: 0.973632 Evaluation's auc: 0.837608 [1552] Train's auc: 0.973645 Evaluation's auc: 0.837607 [1553] Train's auc: 0.973666 Evaluation's auc: 0.837586 [1554] Train's auc: 0.973679 Evaluation's auc: 0.837618 [1555] Train's auc: 0.973682 Evaluation's auc: 0.837609 [1556] Train's auc: 0.973725 Evaluation's auc: 0.837631 [1557] Train's auc: 0.973754 Evaluation's auc: 0.837584 [1558] Train's auc: 0.973775 Evaluation's auc: 0.837582 [1559] Train's auc: 0.973792 Evaluation's auc: 0.837562 [1560] Train's auc: 0.973816 Evaluation's auc: 0.83755 [1561] Train's auc: 0.973829 Evaluation's auc: 0.83754 [1562] Train's auc: 0.973868 Evaluation's auc: 0.837534 [1563] Train's auc: 0.973876 Evaluation's auc: 0.837527 [1564] Train's auc: 0.973888 Evaluation's auc: 0.837519 [1565] Train's auc: 0.973911 Evaluation's auc: 0.837474 [1566] Train's auc: 0.973935 Evaluation's auc: 0.837467 [1567] Train's auc: 0.973937 Evaluation's auc: 0.837464 [1568] Train's auc: 0.973976 Evaluation's auc: 0.837468 [1569] Train's auc: 0.973997 Evaluation's auc: 0.837464 [1570] Train's auc: 0.973998 Evaluation's auc: 0.837469 [1571] Train's auc: 0.974017 Evaluation's auc: 0.837459 [1572] Train's auc: 0.974025 Evaluation's auc: 0.837457 [1573] Train's auc: 0.974062 Evaluation's auc: 0.837449 [1574] Train's auc: 0.974074 Evaluation's auc: 0.837458 [1575] Train's auc: 0.974091 Evaluation's auc: 0.837466 [1576] Train's auc: 0.974109 Evaluation's auc: 0.83743 [1577] Train's auc: 0.974134 Evaluation's auc: 0.837467 [1578] Train's auc: 0.974161 Evaluation's auc: 0.837475 [1579] Train's auc: 0.974185 Evaluation's auc: 0.837463 [1580] Train's auc: 0.974193 Evaluation's auc: 0.837465 [1581] Train's auc: 0.974213 Evaluation's auc: 0.837416 [1582] Train's auc: 0.974233 Evaluation's auc: 0.837392 [1583] Train's auc: 0.974265 Evaluation's auc: 0.8374 [1584] Train's auc: 0.974292 Evaluation's auc: 0.837381 [1585] Train's auc: 0.974303 Evaluation's auc: 0.837369 [1586] Train's auc: 0.974328 Evaluation's auc: 0.837362 [1587] Train's auc: 0.974356 Evaluation's auc: 0.837391 [1588] Train's auc: 0.97436 Evaluation's auc: 0.837404 [1589] Train's auc: 0.974381 Evaluation's auc: 0.837414 [1590] Train's auc: 0.974391 Evaluation's auc: 0.837412 [1591] Train's auc: 0.974397 Evaluation's auc: 0.837394 [1592] Train's auc: 0.974405 Evaluation's auc: 0.837399 [1593] Train's auc: 0.974422 Evaluation's auc: 0.837386 [1594] Train's auc: 0.974427 Evaluation's auc: 0.837424 [1595] Train's auc: 0.974442 Evaluation's auc: 0.837443 [1596] Train's auc: 0.974471 Evaluation's auc: 0.8374 [1597] Train's auc: 0.974481 Evaluation's auc: 0.837427 [1598] Train's auc: 0.974494 Evaluation's auc: 0.837432 [1599] Train's auc: 0.974524 Evaluation's auc: 0.837427 [1600] Train's auc: 0.974546 Evaluation's auc: 0.837439 [1601] Train's auc: 0.974568 Evaluation's auc: 0.83743 [1602] Train's auc: 0.974578 Evaluation's auc: 0.837446 [1603] Train's auc: 0.974605 Evaluation's auc: 0.837424 [1604] Train's auc: 0.974623 Evaluation's auc: 0.837425 [1605] Train's auc: 0.974634 Evaluation's auc: 0.837441 [1606] Train's auc: 0.974647 Evaluation's auc: 0.837441 [1607] Train's auc: 0.974653 Evaluation's auc: 0.837434 [1608] Train's auc: 0.97468 Evaluation's auc: 0.837461 [1609] Train's auc: 0.974698 Evaluation's auc: 0.837458 [1610] Train's auc: 0.974737 Evaluation's auc: 0.837473 [1611] Train's auc: 0.974756 Evaluation's auc: 0.837424 [1612] Train's auc: 0.974759 Evaluation's auc: 0.837429 [1613] Train's auc: 0.974779 Evaluation's auc: 0.837468 [1614] Train's auc: 0.974787 Evaluation's auc: 0.837485 [1615] Train's auc: 0.974813 Evaluation's auc: 0.837505 [1616] Train's auc: 0.974852 Evaluation's auc: 0.837488 [1617] Train's auc: 0.974859 Evaluation's auc: 0.837465 [1618] Train's auc: 0.97488 Evaluation's auc: 0.837446 [1619] Train's auc: 0.9749 Evaluation's auc: 0.837456 [1620] Train's auc: 0.974913 Evaluation's auc: 0.837454 [1621] Train's auc: 0.974933 Evaluation's auc: 0.83742 [1622] Train's auc: 0.974941 Evaluation's auc: 0.837414 [1623] Train's auc: 0.974964 Evaluation's auc: 0.837432 [1624] Train's auc: 0.974969 Evaluation's auc: 0.837439 [1625] Train's auc: 0.974996 Evaluation's auc: 0.837411 [1626] Train's auc: 0.97501 Evaluation's auc: 0.837436 [1627] Train's auc: 0.975035 Evaluation's auc: 0.837439 [1628] Train's auc: 0.975053 Evaluation's auc: 0.837464 [1629] Train's auc: 0.975059 Evaluation's auc: 0.837456 [1630] Train's auc: 0.97507 Evaluation's auc: 0.837441 [1631] Train's auc: 0.975109 Evaluation's auc: 0.83739 [1632] Train's auc: 0.975119 Evaluation's auc: 0.837369 [1633] Train's auc: 0.975156 Evaluation's auc: 0.837306 [1634] Train's auc: 0.975191 Evaluation's auc: 0.837293 [1635] Train's auc: 0.97521 Evaluation's auc: 0.837286 [1636] Train's auc: 0.975234 Evaluation's auc: 0.837292 [1637] Train's auc: 0.975253 Evaluation's auc: 0.83732 [1638] Train's auc: 0.975258 Evaluation's auc: 0.837314 [1639] Train's auc: 0.975293 Evaluation's auc: 0.83733 [1640] Train's auc: 0.975309 Evaluation's auc: 0.837313 [1641] Train's auc: 0.975342 Evaluation's auc: 0.837326 [1642] Train's auc: 0.975377 Evaluation's auc: 0.837313 [1643] Train's auc: 0.975402 Evaluation's auc: 0.83731 [1644] Train's auc: 0.975422 Evaluation's auc: 0.837318 [1645] Train's auc: 0.975441 Evaluation's auc: 0.837306 [1646] Train's auc: 0.975438 Evaluation's auc: 0.837311 [1647] Train's auc: 0.975452 Evaluation's auc: 0.837307 [1648] Train's auc: 0.975457 Evaluation's auc: 0.837305 [1649] Train's auc: 0.975465 Evaluation's auc: 0.837307 [1650] Train's auc: 0.975471 Evaluation's auc: 0.837344 [1651] Train's auc: 0.975476 Evaluation's auc: 0.837336 [1652] Train's auc: 0.975482 Evaluation's auc: 0.837316 [1653] Train's auc: 0.975494 Evaluation's auc: 0.837309 [1654] Train's auc: 0.97553 Evaluation's auc: 0.837312 [1655] Train's auc: 0.975545 Evaluation's auc: 0.837299 [1656] Train's auc: 0.975558 Evaluation's auc: 0.837273 [1657] Train's auc: 0.97557 Evaluation's auc: 0.837271 [1658] Train's auc: 0.975594 Evaluation's auc: 0.837213 [1659] Train's auc: 0.975612 Evaluation's auc: 0.837193 [1660] Train's auc: 0.975628 Evaluation's auc: 0.837189 [1661] Train's auc: 0.975643 Evaluation's auc: 0.837191 [1662] Train's auc: 0.975665 Evaluation's auc: 0.837161 [1663] Train's auc: 0.975704 Evaluation's auc: 0.837181 [1664] Train's auc: 0.975716 Evaluation's auc: 0.837158 [1665] Train's auc: 0.97573 Evaluation's auc: 0.837175 [1666] Train's auc: 0.975755 Evaluation's auc: 0.837169 [1667] Train's auc: 0.97577 Evaluation's auc: 0.837128 [1668] Train's auc: 0.975782 Evaluation's auc: 0.837123 [1669] Train's auc: 0.975787 Evaluation's auc: 0.83713 [1670] Train's auc: 0.975806 Evaluation's auc: 0.837138 [1671] Train's auc: 0.975816 Evaluation's auc: 0.837161 [1672] Train's auc: 0.975829 Evaluation's auc: 0.837166 [1673] Train's auc: 0.975841 Evaluation's auc: 0.837135 [1674] Train's auc: 0.975836 Evaluation's auc: 0.837141 [1675] Train's auc: 0.97585 Evaluation's auc: 0.837127 [1676] Train's auc: 0.975867 Evaluation's auc: 0.837109 [1677] Train's auc: 0.975882 Evaluation's auc: 0.837118 [1678] Train's auc: 0.97591 Evaluation's auc: 0.837091 [1679] Train's auc: 0.975918 Evaluation's auc: 0.837096 [1680] Train's auc: 0.975929 Evaluation's auc: 0.83714 [1681] Train's auc: 0.975959 Evaluation's auc: 0.837146 [1682] Train's auc: 0.975976 Evaluation's auc: 0.837137 [1683] Train's auc: 0.975983 Evaluation's auc: 0.837139 [1684] Train's auc: 0.97599 Evaluation's auc: 0.83714 [1685] Train's auc: 0.97601 Evaluation's auc: 0.837105 [1686] Train's auc: 0.976032 Evaluation's auc: 0.837071 [1687] Train's auc: 0.976056 Evaluation's auc: 0.837043 [1688] Train's auc: 0.976075 Evaluation's auc: 0.837082 [1689] Train's auc: 0.976081 Evaluation's auc: 0.837071 [1690] Train's auc: 0.976094 Evaluation's auc: 0.837044 [1691] Train's auc: 0.976099 Evaluation's auc: 0.83704 [1692] Train's auc: 0.976127 Evaluation's auc: 0.837024 [1693] Train's auc: 0.976145 Evaluation's auc: 0.837022 [1694] Train's auc: 0.97616 Evaluation's auc: 0.836989 [1695] Train's auc: 0.976163 Evaluation's auc: 0.836995 [1696] Train's auc: 0.976169 Evaluation's auc: 0.837006 [1697] Train's auc: 0.976191 Evaluation's auc: 0.836965 [1698] Train's auc: 0.976226 Evaluation's auc: 0.836957 [1699] Train's auc: 0.976239 Evaluation's auc: 0.83696 [1700] Train's auc: 0.976276 Evaluation's auc: 0.836956 [1701] Train's auc: 0.976301 Evaluation's auc: 0.836978 [1702] Train's auc: 0.976322 Evaluation's auc: 0.836993 [1703] Train's auc: 0.976343 Evaluation's auc: 0.836975 [1704] Train's auc: 0.976371 Evaluation's auc: 0.836977 [1705] Train's auc: 0.976384 Evaluation's auc: 0.836931 [1706] Train's auc: 0.97639 Evaluation's auc: 0.836919 [1707] Train's auc: 0.976414 Evaluation's auc: 0.836923 [1708] Train's auc: 0.976426 Evaluation's auc: 0.836918 [1709] Train's auc: 0.976438 Evaluation's auc: 0.836928 [1710] Train's auc: 0.976457 Evaluation's auc: 0.83687 [1711] Train's auc: 0.976477 Evaluation's auc: 0.836858 [1712] Train's auc: 0.976479 Evaluation's auc: 0.836853 [1713] Train's auc: 0.976478 Evaluation's auc: 0.836852 [1714] Train's auc: 0.976477 Evaluation's auc: 0.836854 [1715] Train's auc: 0.976497 Evaluation's auc: 0.836911 [1716] Train's auc: 0.976507 Evaluation's auc: 0.836896 [1717] Train's auc: 0.97652 Evaluation's auc: 0.836891 [1718] Train's auc: 0.976539 Evaluation's auc: 0.836869 [1719] Train's auc: 0.976545 Evaluation's auc: 0.836878 [1720] Train's auc: 0.976557 Evaluation's auc: 0.836929 [1721] Train's auc: 0.976587 Evaluation's auc: 0.836907 [1722] Train's auc: 0.97661 Evaluation's auc: 0.836914 [1723] Train's auc: 0.976638 Evaluation's auc: 0.8369 [1724] Train's auc: 0.976653 Evaluation's auc: 0.836915 [1725] Train's auc: 0.976662 Evaluation's auc: 0.836907 [1726] Train's auc: 0.976668 Evaluation's auc: 0.836902 [1727] Train's auc: 0.976681 Evaluation's auc: 0.836907 [1728] Train's auc: 0.976693 Evaluation's auc: 0.836916 [1729] Train's auc: 0.976709 Evaluation's auc: 0.836907 [1730] Train's auc: 0.976733 Evaluation's auc: 0.836905 [1731] Train's auc: 0.976752 Evaluation's auc: 0.836911 [1732] Train's auc: 0.976772 Evaluation's auc: 0.836923 [1733] Train's auc: 0.976778 Evaluation's auc: 0.836913 [1734] Train's auc: 0.976785 Evaluation's auc: 0.836888 [1735] Train's auc: 0.976799 Evaluation's auc: 0.83689 [1736] Train's auc: 0.976804 Evaluation's auc: 0.836878 [1737] Train's auc: 0.976828 Evaluation's auc: 0.836859 [1738] Train's auc: 0.97683 Evaluation's auc: 0.836858 [1739] Train's auc: 0.976845 Evaluation's auc: 0.836862 [1740] Train's auc: 0.976848 Evaluation's auc: 0.836864 [1741] Train's auc: 0.976863 Evaluation's auc: 0.836855 [1742] Train's auc: 0.97688 Evaluation's auc: 0.836855 [1743] Train's auc: 0.976897 Evaluation's auc: 0.836864 [1744] Train's auc: 0.976907 Evaluation's auc: 0.836856 [1745] Train's auc: 0.976943 Evaluation's auc: 0.836807 [1746] Train's auc: 0.97696 Evaluation's auc: 0.836788 [1747] Train's auc: 0.976958 Evaluation's auc: 0.836786 [1748] Train's auc: 0.976984 Evaluation's auc: 0.836793 [1749] Train's auc: 0.976997 Evaluation's auc: 0.836794 [1750] Train's auc: 0.977017 Evaluation's auc: 0.836814 [1751] Train's auc: 0.977033 Evaluation's auc: 0.836836 [1752] Train's auc: 0.977059 Evaluation's auc: 0.83682 [1753] Train's auc: 0.977073 Evaluation's auc: 0.836793 [1754] Train's auc: 0.977088 Evaluation's auc: 0.83679 [1755] Train's auc: 0.977105 Evaluation's auc: 0.836763 [1756] Train's auc: 0.977125 Evaluation's auc: 0.836751 [1757] Train's auc: 0.977143 Evaluation's auc: 0.836749 [1758] Train's auc: 0.977163 Evaluation's auc: 0.836769 [1759] Train's auc: 0.977177 Evaluation's auc: 0.836711 [1760] Train's auc: 0.9772 Evaluation's auc: 0.836704 [1761] Train's auc: 0.97721 Evaluation's auc: 0.836734 [1762] Train's auc: 0.977222 Evaluation's auc: 0.836731 [1763] Train's auc: 0.977244 Evaluation's auc: 0.836703 [1764] Train's auc: 0.977274 Evaluation's auc: 0.836723 [1765] Train's auc: 0.977289 Evaluation's auc: 0.836687 [1766] Train's auc: 0.977305 Evaluation's auc: 0.836667 [1767] Train's auc: 0.977318 Evaluation's auc: 0.836654 [1768] Train's auc: 0.977329 Evaluation's auc: 0.836648 [1769] Train's auc: 0.977345 Evaluation's auc: 0.836651 [1770] Train's auc: 0.977347 Evaluation's auc: 0.836652 [1771] Train's auc: 0.97736 Evaluation's auc: 0.836618 [1772] Train's auc: 0.977371 Evaluation's auc: 0.836603 [1773] Train's auc: 0.977377 Evaluation's auc: 0.836606 [1774] Train's auc: 0.977391 Evaluation's auc: 0.836595 [1775] Train's auc: 0.977413 Evaluation's auc: 0.836593 [1776] Train's auc: 0.977428 Evaluation's auc: 0.836593 [1777] Train's auc: 0.977459 Evaluation's auc: 0.836502 [1778] Train's auc: 0.97748 Evaluation's auc: 0.836471 [1779] Train's auc: 0.97748 Evaluation's auc: 0.836491 [1780] Train's auc: 0.977502 Evaluation's auc: 0.836523 [1781] Train's auc: 0.977512 Evaluation's auc: 0.836501 [1782] Train's auc: 0.977511 Evaluation's auc: 0.83651 [1783] Train's auc: 0.977526 Evaluation's auc: 0.83648 [1784] Train's auc: 0.977534 Evaluation's auc: 0.83648 [1785] Train's auc: 0.977535 Evaluation's auc: 0.836479 [1786] Train's auc: 0.977547 Evaluation's auc: 0.836484 [1787] Train's auc: 0.977557 Evaluation's auc: 0.836509 [1788] Train's auc: 0.977585 Evaluation's auc: 0.836529 [1789] Train's auc: 0.977607 Evaluation's auc: 0.8365 [1790] Train's auc: 0.977618 Evaluation's auc: 0.836464 [1791] Train's auc: 0.977631 Evaluation's auc: 0.836456 [1792] Train's auc: 0.97765 Evaluation's auc: 0.836437 [1793] Train's auc: 0.977655 Evaluation's auc: 0.836436 [1794] Train's auc: 0.977659 Evaluation's auc: 0.836433 [1795] Train's auc: 0.977669 Evaluation's auc: 0.836417 [1796] Train's auc: 0.977676 Evaluation's auc: 0.836415 [1797] Train's auc: 0.977689 Evaluation's auc: 0.83645 [1798] Train's auc: 0.977695 Evaluation's auc: 0.836457 [1799] Train's auc: 0.977714 Evaluation's auc: 0.836451 [1800] Train's auc: 0.97773 Evaluation's auc: 0.836441 [1801] Train's auc: 0.977767 Evaluation's auc: 0.836449 [1802] Train's auc: 0.977787 Evaluation's auc: 0.836463 [1803] Train's auc: 0.977807 Evaluation's auc: 0.836451 [1804] Train's auc: 0.977809 Evaluation's auc: 0.836445 [1805] Train's auc: 0.977819 Evaluation's auc: 0.836466 [1806] Train's auc: 0.977847 Evaluation's auc: 0.836442 [1807] Train's auc: 0.977861 Evaluation's auc: 0.83643 [1808] Train's auc: 0.977868 Evaluation's auc: 0.836444 [1809] Train's auc: 0.977868 Evaluation's auc: 0.836436 [1810] Train's auc: 0.977879 Evaluation's auc: 0.836483 [1811] Train's auc: 0.977891 Evaluation's auc: 0.836457 [1812] Train's auc: 0.977905 Evaluation's auc: 0.836466 [1813] Train's auc: 0.977924 Evaluation's auc: 0.836442 [1814] Train's auc: 0.97793 Evaluation's auc: 0.836417 [1815] Train's auc: 0.977943 Evaluation's auc: 0.836475 [1816] Train's auc: 0.977968 Evaluation's auc: 0.836447 [1817] Train's auc: 0.977978 Evaluation's auc: 0.836458 [1818] Train's auc: 0.977993 Evaluation's auc: 0.836466 [1819] Train's auc: 0.978017 Evaluation's auc: 0.83645 [1820] Train's auc: 0.978027 Evaluation's auc: 0.836467 [1821] Train's auc: 0.978049 Evaluation's auc: 0.836451 [1822] Train's auc: 0.978053 Evaluation's auc: 0.836447 [1823] Train's auc: 0.97806 Evaluation's auc: 0.836473 [1824] Train's auc: 0.978077 Evaluation's auc: 0.83646 [1825] Train's auc: 0.978096 Evaluation's auc: 0.836464 [1826] Train's auc: 0.978112 Evaluation's auc: 0.836455 [1827] Train's auc: 0.978123 Evaluation's auc: 0.836471 [1828] Train's auc: 0.978122 Evaluation's auc: 0.83649 [1829] Train's auc: 0.97813 Evaluation's auc: 0.836514 [1830] Train's auc: 0.978146 Evaluation's auc: 0.836447 [1831] Train's auc: 0.978165 Evaluation's auc: 0.836426 [1832] Train's auc: 0.978177 Evaluation's auc: 0.836427 [1833] Train's auc: 0.978194 Evaluation's auc: 0.836447 [1834] Train's auc: 0.978208 Evaluation's auc: 0.836425 [1835] Train's auc: 0.978217 Evaluation's auc: 0.83644 [1836] Train's auc: 0.978233 Evaluation's auc: 0.836414 [1837] Train's auc: 0.97825 Evaluation's auc: 0.836411 [1838] Train's auc: 0.978265 Evaluation's auc: 0.836394 [1839] Train's auc: 0.978282 Evaluation's auc: 0.836379 [1840] Train's auc: 0.978293 Evaluation's auc: 0.836377 [1841] Train's auc: 0.978305 Evaluation's auc: 0.836374 [1842] Train's auc: 0.978326 Evaluation's auc: 0.836376 [1843] Train's auc: 0.97834 Evaluation's auc: 0.836346 [1844] Train's auc: 0.978351 Evaluation's auc: 0.836343 [1845] Train's auc: 0.978352 Evaluation's auc: 0.83634 [1846] Train's auc: 0.97837 Evaluation's auc: 0.836321 [1847] Train's auc: 0.978385 Evaluation's auc: 0.836321 [1848] Train's auc: 0.978395 Evaluation's auc: 0.83633 [1849] Train's auc: 0.978408 Evaluation's auc: 0.836317 [1850] Train's auc: 0.978425 Evaluation's auc: 0.83634 [1851] Train's auc: 0.978436 Evaluation's auc: 0.836356 [1852] Train's auc: 0.978447 Evaluation's auc: 0.836344 [1853] Train's auc: 0.978467 Evaluation's auc: 0.8363 [1854] Train's auc: 0.978474 Evaluation's auc: 0.836281 [1855] Train's auc: 0.978481 Evaluation's auc: 0.836293 [1856] Train's auc: 0.978504 Evaluation's auc: 0.836308 [1857] Train's auc: 0.978509 Evaluation's auc: 0.836315 [1858] Train's auc: 0.978517 Evaluation's auc: 0.836338 [1859] Train's auc: 0.978534 Evaluation's auc: 0.836311 [1860] Train's auc: 0.978549 Evaluation's auc: 0.836337 [1861] Train's auc: 0.978559 Evaluation's auc: 0.836311 [1862] Train's auc: 0.978567 Evaluation's auc: 0.836309 [1863] Train's auc: 0.978591 Evaluation's auc: 0.836311 [1864] Train's auc: 0.978605 Evaluation's auc: 0.83632 [1865] Train's auc: 0.97862 Evaluation's auc: 0.836324 [1866] Train's auc: 0.978634 Evaluation's auc: 0.836276 [1867] Train's auc: 0.978639 Evaluation's auc: 0.836277 [1868] Train's auc: 0.97865 Evaluation's auc: 0.836255 [1869] Train's auc: 0.978674 Evaluation's auc: 0.836269 [1870] Train's auc: 0.978707 Evaluation's auc: 0.836257 [1871] Train's auc: 0.978717 Evaluation's auc: 0.836247 [1872] Train's auc: 0.978733 Evaluation's auc: 0.836271 [1873] Train's auc: 0.978734 Evaluation's auc: 0.836289 [1874] Train's auc: 0.978751 Evaluation's auc: 0.836269 [1875] Train's auc: 0.978767 Evaluation's auc: 0.836301 [1876] Train's auc: 0.978782 Evaluation's auc: 0.836315 [1877] Train's auc: 0.978796 Evaluation's auc: 0.836297 [1878] Train's auc: 0.978808 Evaluation's auc: 0.83629 [1879] Train's auc: 0.978836 Evaluation's auc: 0.836315 [1880] Train's auc: 0.978854 Evaluation's auc: 0.836295 [1881] Train's auc: 0.978873 Evaluation's auc: 0.836344 [1882] Train's auc: 0.978897 Evaluation's auc: 0.836351 [1883] Train's auc: 0.978917 Evaluation's auc: 0.836375 [1884] Train's auc: 0.978925 Evaluation's auc: 0.836381 [1885] Train's auc: 0.97893 Evaluation's auc: 0.836368 [1886] Train's auc: 0.978943 Evaluation's auc: 0.836333 [1887] Train's auc: 0.978954 Evaluation's auc: 0.836328 [1888] Train's auc: 0.978941 Evaluation's auc: 0.836365 [1889] Train's auc: 0.978943 Evaluation's auc: 0.836391 [1890] Train's auc: 0.978954 Evaluation's auc: 0.836379 [1891] Train's auc: 0.978972 Evaluation's auc: 0.836357 [1892] Train's auc: 0.978986 Evaluation's auc: 0.836393 [1893] Train's auc: 0.979006 Evaluation's auc: 0.836389 [1894] Train's auc: 0.979012 Evaluation's auc: 0.836371 [1895] Train's auc: 0.979029 Evaluation's auc: 0.836381 [1896] Train's auc: 0.979043 Evaluation's auc: 0.836362 [1897] Train's auc: 0.979049 Evaluation's auc: 0.836374 [1898] Train's auc: 0.97907 Evaluation's auc: 0.836382 [1899] Train's auc: 0.979076 Evaluation's auc: 0.836394 [1900] Train's auc: 0.979083 Evaluation's auc: 0.836394 [1901] Train's auc: 0.979095 Evaluation's auc: 0.836389 [1902] Train's auc: 0.979105 Evaluation's auc: 0.836371 [1903] Train's auc: 0.979119 Evaluation's auc: 0.836327 [1904] Train's auc: 0.979137 Evaluation's auc: 0.836324 [1905] Train's auc: 0.97915 Evaluation's auc: 0.836346 [1906] Train's auc: 0.979172 Evaluation's auc: 0.836371 [1907] Train's auc: 0.97918 Evaluation's auc: 0.836352 [1908] Train's auc: 0.979182 Evaluation's auc: 0.836351 [1909] Train's auc: 0.979193 Evaluation's auc: 0.836327 [1910] Train's auc: 0.979211 Evaluation's auc: 0.836283 [1911] Train's auc: 0.979227 Evaluation's auc: 0.836275 [1912] Train's auc: 0.979243 Evaluation's auc: 0.836262 [1913] Train's auc: 0.979262 Evaluation's auc: 0.836237 [1914] Train's auc: 0.979267 Evaluation's auc: 0.836243 [1915] Train's auc: 0.979283 Evaluation's auc: 0.836218 [1916] Train's auc: 0.979272 Evaluation's auc: 0.836286 [1917] Train's auc: 0.979293 Evaluation's auc: 0.836255 [1918] Train's auc: 0.979302 Evaluation's auc: 0.836258 [1919] Train's auc: 0.979307 Evaluation's auc: 0.83623 [1920] Train's auc: 0.979318 Evaluation's auc: 0.836238 [1921] Train's auc: 0.97932 Evaluation's auc: 0.836233 [1922] Train's auc: 0.979335 Evaluation's auc: 0.836247 [1923] Train's auc: 0.979345 Evaluation's auc: 0.836254 [1924] Train's auc: 0.97936 Evaluation's auc: 0.836249 [1925] Train's auc: 0.979363 Evaluation's auc: 0.836243 [1926] Train's auc: 0.979369 Evaluation's auc: 0.836226 [1927] Train's auc: 0.979376 Evaluation's auc: 0.836226 [1928] Train's auc: 0.979385 Evaluation's auc: 0.836211 [1929] Train's auc: 0.979387 Evaluation's auc: 0.836221 [1930] Train's auc: 0.979405 Evaluation's auc: 0.836203 [1931] Train's auc: 0.979414 Evaluation's auc: 0.836225 [1932] Train's auc: 0.979422 Evaluation's auc: 0.836223 [1933] Train's auc: 0.97943 Evaluation's auc: 0.83622 [1934] Train's auc: 0.979435 Evaluation's auc: 0.836225 [1935] Train's auc: 0.979435 Evaluation's auc: 0.836224 [1936] Train's auc: 0.979439 Evaluation's auc: 0.836213 [1937] Train's auc: 0.979442 Evaluation's auc: 0.836208 [1938] Train's auc: 0.979455 Evaluation's auc: 0.836198 [1939] Train's auc: 0.979472 Evaluation's auc: 0.83618 [1940] Train's auc: 0.979495 Evaluation's auc: 0.836137 [1941] Train's auc: 0.979499 Evaluation's auc: 0.836137 [1942] Train's auc: 0.979514 Evaluation's auc: 0.83616 [1943] Train's auc: 0.979526 Evaluation's auc: 0.836173 [1944] Train's auc: 0.979543 Evaluation's auc: 0.836196 [1945] Train's auc: 0.979554 Evaluation's auc: 0.836182 [1946] Train's auc: 0.979554 Evaluation's auc: 0.836157 [1947] Train's auc: 0.979556 Evaluation's auc: 0.836153 [1948] Train's auc: 0.979568 Evaluation's auc: 0.836168 [1949] Train's auc: 0.979574 Evaluation's auc: 0.836162 [1950] Train's auc: 0.979579 Evaluation's auc: 0.836166 [1951] Train's auc: 0.979585 Evaluation's auc: 0.836167 [1952] Train's auc: 0.979598 Evaluation's auc: 0.836141 [1953] Train's auc: 0.979598 Evaluation's auc: 0.836127 [1954] Train's auc: 0.979616 Evaluation's auc: 0.83609 [1955] Train's auc: 0.979623 Evaluation's auc: 0.836065 [1956] Train's auc: 0.979637 Evaluation's auc: 0.836037 [1957] Train's auc: 0.979654 Evaluation's auc: 0.836013 [1958] Train's auc: 0.979668 Evaluation's auc: 0.836008 [1959] Train's auc: 0.979678 Evaluation's auc: 0.836006 [1960] Train's auc: 0.979678 Evaluation's auc: 0.836009 [1961] Train's auc: 0.979683 Evaluation's auc: 0.835992 [1962] Train's auc: 0.979685 Evaluation's auc: 0.836021 [1963] Train's auc: 0.979691 Evaluation's auc: 0.836021 [1964] Train's auc: 0.979711 Evaluation's auc: 0.835998 [1965] Train's auc: 0.979722 Evaluation's auc: 0.836027 [1966] Train's auc: 0.979736 Evaluation's auc: 0.835995 [1967] Train's auc: 0.979752 Evaluation's auc: 0.835998 [1968] Train's auc: 0.979767 Evaluation's auc: 0.836001 [1969] Train's auc: 0.979779 Evaluation's auc: 0.83596 [1970] Train's auc: 0.979794 Evaluation's auc: 0.835958 [1971] Train's auc: 0.979813 Evaluation's auc: 0.835963 [1972] Train's auc: 0.979833 Evaluation's auc: 0.835969 [1973] Train's auc: 0.979865 Evaluation's auc: 0.835993 [1974] Train's auc: 0.979861 Evaluation's auc: 0.835998 [1975] Train's auc: 0.979874 Evaluation's auc: 0.836011 [1976] Train's auc: 0.97987 Evaluation's auc: 0.836009 [1977] Train's auc: 0.979876 Evaluation's auc: 0.835983 [1978] Train's auc: 0.979874 Evaluation's auc: 0.836029 [1979] Train's auc: 0.979885 Evaluation's auc: 0.836022 [1980] Train's auc: 0.979886 Evaluation's auc: 0.836006 [1981] Train's auc: 0.9799 Evaluation's auc: 0.836014 [1982] Train's auc: 0.979942 Evaluation's auc: 0.836064 [1983] Train's auc: 0.979956 Evaluation's auc: 0.836022 [1984] Train's auc: 0.97998 Evaluation's auc: 0.835996 [1985] Train's auc: 0.979983 Evaluation's auc: 0.835982 [1986] Train's auc: 0.979984 Evaluation's auc: 0.835984 [1987] Train's auc: 0.979992 Evaluation's auc: 0.835983 [1988] Train's auc: 0.98 Evaluation's auc: 0.835977 [1989] Train's auc: 0.980027 Evaluation's auc: 0.835974 [1990] Train's auc: 0.980023 Evaluation's auc: 0.835977 [1991] Train's auc: 0.98003 Evaluation's auc: 0.836004 [1992] Train's auc: 0.980037 Evaluation's auc: 0.835987 [1993] Train's auc: 0.98005 Evaluation's auc: 0.835999 [1994] Train's auc: 0.98005 Evaluation's auc: 0.835987 [1995] Train's auc: 0.980064 Evaluation's auc: 0.835964 [1996] Train's auc: 0.980073 Evaluation's auc: 0.836006 [1997] Train's auc: 0.980079 Evaluation's auc: 0.835985 [1998] Train's auc: 0.980086 Evaluation's auc: 0.836004 [1999] Train's auc: 0.980099 Evaluation's auc: 0.835991 [2000] Train's auc: 0.980113 Evaluation's auc: 0.835976 [2001] Train's auc: 0.980127 Evaluation's auc: 0.835974 [2002] Train's auc: 0.980137 Evaluation's auc: 0.835949 [2003] Train's auc: 0.980143 Evaluation's auc: 0.835962 [2004] Train's auc: 0.980166 Evaluation's auc: 0.835926 [2005] Train's auc: 0.980165 Evaluation's auc: 0.835968 [2006] Train's auc: 0.980172 Evaluation's auc: 0.835985 [2007] Train's auc: 0.980181 Evaluation's auc: 0.835949 [2008] Train's auc: 0.980195 Evaluation's auc: 0.83593 [2009] Train's auc: 0.9802 Evaluation's auc: 0.835938 [2010] Train's auc: 0.980206 Evaluation's auc: 0.835933 [2011] Train's auc: 0.980214 Evaluation's auc: 0.835942 [2012] Train's auc: 0.980217 Evaluation's auc: 0.835942 [2013] Train's auc: 0.980217 Evaluation's auc: 0.835936 [2014] Train's auc: 0.980237 Evaluation's auc: 0.835925 [2015] Train's auc: 0.980245 Evaluation's auc: 0.835912 [2016] Train's auc: 0.98026 Evaluation's auc: 0.835918 [2017] Train's auc: 0.980262 Evaluation's auc: 0.835917 [2018] Train's auc: 0.980274 Evaluation's auc: 0.83593 [2019] Train's auc: 0.980288 Evaluation's auc: 0.835936 [2020] Train's auc: 0.980307 Evaluation's auc: 0.835954 [2021] Train's auc: 0.980314 Evaluation's auc: 0.835945 [2022] Train's auc: 0.980319 Evaluation's auc: 0.83595 [2023] Train's auc: 0.980318 Evaluation's auc: 0.835974 [2024] Train's auc: 0.98032 Evaluation's auc: 0.835992 [2025] Train's auc: 0.980313 Evaluation's auc: 0.836003 [2026] Train's auc: 0.980332 Evaluation's auc: 0.835991 [2027] Train's auc: 0.98034 Evaluation's auc: 0.835989 [2028] Train's auc: 0.980354 Evaluation's auc: 0.835996 [2029] Train's auc: 0.980359 Evaluation's auc: 0.835976 [2030] Train's auc: 0.980384 Evaluation's auc: 0.835963 [2031] Train's auc: 0.980401 Evaluation's auc: 0.835951 [2032] Train's auc: 0.980397 Evaluation's auc: 0.835962 [2033] Train's auc: 0.980417 Evaluation's auc: 0.835944 [2034] Train's auc: 0.980446 Evaluation's auc: 0.835925 [2035] Train's auc: 0.980449 Evaluation's auc: 0.835952 [2036] Train's auc: 0.980461 Evaluation's auc: 0.835926 [2037] Train's auc: 0.980473 Evaluation's auc: 0.83594 [2038] Train's auc: 0.980476 Evaluation's auc: 0.835951 [2039] Train's auc: 0.98049 Evaluation's auc: 0.835966 [2040] Train's auc: 0.980506 Evaluation's auc: 0.835969 [2041] Train's auc: 0.980511 Evaluation's auc: 0.83598 [2042] Train's auc: 0.980526 Evaluation's auc: 0.83595 [2043] Train's auc: 0.980529 Evaluation's auc: 0.835943 [2044] Train's auc: 0.980537 Evaluation's auc: 0.835945 [2045] Train's auc: 0.980548 Evaluation's auc: 0.835937 [2046] Train's auc: 0.980565 Evaluation's auc: 0.83597 [2047] Train's auc: 0.980567 Evaluation's auc: 0.835961 [2048] Train's auc: 0.980596 Evaluation's auc: 0.835973 [2049] Train's auc: 0.98062 Evaluation's auc: 0.835957 [2050] Train's auc: 0.980621 Evaluation's auc: 0.83596 [2051] Train's auc: 0.980649 Evaluation's auc: 0.835975 [2052] Train's auc: 0.980665 Evaluation's auc: 0.835969 [2053] Train's auc: 0.980677 Evaluation's auc: 0.835986 [2054] Train's auc: 0.980685 Evaluation's auc: 0.835992 [2055] Train's auc: 0.980702 Evaluation's auc: 0.836002 [2056] Train's auc: 0.980721 Evaluation's auc: 0.836022 [2057] Train's auc: 0.980723 Evaluation's auc: 0.836028 [2058] Train's auc: 0.980728 Evaluation's auc: 0.836018 [2059] Train's auc: 0.980743 Evaluation's auc: 0.835969 [2060] Train's auc: 0.980749 Evaluation's auc: 0.836004 [2061] Train's auc: 0.980752 Evaluation's auc: 0.835996 [2062] Train's auc: 0.980752 Evaluation's auc: 0.835991 [2063] Train's auc: 0.980771 Evaluation's auc: 0.835957 [2064] Train's auc: 0.980786 Evaluation's auc: 0.835927 [2065] Train's auc: 0.980806 Evaluation's auc: 0.835918 [2066] Train's auc: 0.980824 Evaluation's auc: 0.835887 [2067] Train's auc: 0.980841 Evaluation's auc: 0.835896 [2068] Train's auc: 0.980842 Evaluation's auc: 0.835889 [2069] Train's auc: 0.980849 Evaluation's auc: 0.835874 [2070] Train's auc: 0.980847 Evaluation's auc: 0.835885 [2071] Train's auc: 0.980849 Evaluation's auc: 0.835884 [2072] Train's auc: 0.98087 Evaluation's auc: 0.835854 [2073] Train's auc: 0.980871 Evaluation's auc: 0.835843 [2074] Train's auc: 0.980874 Evaluation's auc: 0.835849 [2075] Train's auc: 0.980891 Evaluation's auc: 0.835846 [2076] Train's auc: 0.980911 Evaluation's auc: 0.83585 [2077] Train's auc: 0.980921 Evaluation's auc: 0.835839 [2078] Train's auc: 0.980933 Evaluation's auc: 0.835842 [2079] Train's auc: 0.980953 Evaluation's auc: 0.83582 [2080] Train's auc: 0.980965 Evaluation's auc: 0.835806 [2081] Train's auc: 0.980969 Evaluation's auc: 0.83581 [2082] Train's auc: 0.980983 Evaluation's auc: 0.835808 [2083] Train's auc: 0.980986 Evaluation's auc: 0.835807 [2084] Train's auc: 0.980996 Evaluation's auc: 0.835798 [2085] Train's auc: 0.981018 Evaluation's auc: 0.835769 [2086] Train's auc: 0.981015 Evaluation's auc: 0.835769 [2087] Train's auc: 0.981028 Evaluation's auc: 0.835761 [2088] Train's auc: 0.981039 Evaluation's auc: 0.835774 [2089] Train's auc: 0.981057 Evaluation's auc: 0.835787 [2090] Train's auc: 0.981076 Evaluation's auc: 0.83577 [2091] Train's auc: 0.981084 Evaluation's auc: 0.83577 [2092] Train's auc: 0.981092 Evaluation's auc: 0.835741 [2093] Train's auc: 0.981101 Evaluation's auc: 0.835736 [2094] Train's auc: 0.981112 Evaluation's auc: 0.835721 [2095] Train's auc: 0.981121 Evaluation's auc: 0.835722 [2096] Train's auc: 0.981131 Evaluation's auc: 0.835695 [2097] Train's auc: 0.981128 Evaluation's auc: 0.835689 [2098] Train's auc: 0.981139 Evaluation's auc: 0.835685 [2099] Train's auc: 0.981138 Evaluation's auc: 0.835686 [2100] Train's auc: 0.981152 Evaluation's auc: 0.835651 [2101] Train's auc: 0.981157 Evaluation's auc: 0.835629 [2102] Train's auc: 0.981163 Evaluation's auc: 0.835649 [2103] Train's auc: 0.981177 Evaluation's auc: 0.835646 [2104] Train's auc: 0.981182 Evaluation's auc: 0.835636 [2105] Train's auc: 0.981191 Evaluation's auc: 0.835626 [2106] Train's auc: 0.981211 Evaluation's auc: 0.835617 [2107] Train's auc: 0.981227 Evaluation's auc: 0.835631 [2108] Train's auc: 0.981246 Evaluation's auc: 0.835614 [2109] Train's auc: 0.981256 Evaluation's auc: 0.835611 [2110] Train's auc: 0.981259 Evaluation's auc: 0.83565 [2111] Train's auc: 0.98126 Evaluation's auc: 0.83565 [2112] Train's auc: 0.981299 Evaluation's auc: 0.835659 [2113] Train's auc: 0.981306 Evaluation's auc: 0.835622 [2114] Train's auc: 0.981318 Evaluation's auc: 0.835627 [2115] Train's auc: 0.981324 Evaluation's auc: 0.835627 [2116] Train's auc: 0.981337 Evaluation's auc: 0.835629 [2117] Train's auc: 0.98135 Evaluation's auc: 0.835579 [2118] Train's auc: 0.981355 Evaluation's auc: 0.835581 [2119] Train's auc: 0.981372 Evaluation's auc: 0.8356 [2120] Train's auc: 0.98138 Evaluation's auc: 0.835592 [2121] Train's auc: 0.98139 Evaluation's auc: 0.835604 [2122] Train's auc: 0.981435 Evaluation's auc: 0.835637 [2123] Train's auc: 0.981443 Evaluation's auc: 0.835614 [2124] Train's auc: 0.981457 Evaluation's auc: 0.835614 [2125] Train's auc: 0.981473 Evaluation's auc: 0.835619 [2126] Train's auc: 0.981471 Evaluation's auc: 0.835657 [2127] Train's auc: 0.98148 Evaluation's auc: 0.835676 [2128] Train's auc: 0.981498 Evaluation's auc: 0.835647 [2129] Train's auc: 0.981508 Evaluation's auc: 0.835633 [2130] Train's auc: 0.981518 Evaluation's auc: 0.83565 [2131] Train's auc: 0.981521 Evaluation's auc: 0.835657 [2132] Train's auc: 0.981542 Evaluation's auc: 0.835655 [2133] Train's auc: 0.981551 Evaluation's auc: 0.835657 [2134] Train's auc: 0.981549 Evaluation's auc: 0.835648 [2135] Train's auc: 0.981571 Evaluation's auc: 0.8356 [2136] Train's auc: 0.981577 Evaluation's auc: 0.835619 [2137] Train's auc: 0.98157 Evaluation's auc: 0.83563 [2138] Train's auc: 0.981581 Evaluation's auc: 0.835612 [2139] Train's auc: 0.981596 Evaluation's auc: 0.835618 [2140] Train's auc: 0.981598 Evaluation's auc: 0.835619 [2141] Train's auc: 0.98161 Evaluation's auc: 0.835642 [2142] Train's auc: 0.98163 Evaluation's auc: 0.835621 [2143] Train's auc: 0.981644 Evaluation's auc: 0.835628 [2144] Train's auc: 0.981657 Evaluation's auc: 0.835627 [2145] Train's auc: 0.981669 Evaluation's auc: 0.83563 [2146] Train's auc: 0.981679 Evaluation's auc: 0.835656 [2147] Train's auc: 0.981687 Evaluation's auc: 0.835646 [2148] Train's auc: 0.98169 Evaluation's auc: 0.835641 [2149] Train's auc: 0.981692 Evaluation's auc: 0.835639 [2150] Train's auc: 0.981701 Evaluation's auc: 0.835611 [2151] Train's auc: 0.981711 Evaluation's auc: 0.83559 [2152] Train's auc: 0.981723 Evaluation's auc: 0.835577 [2153] Train's auc: 0.981724 Evaluation's auc: 0.835578 [2154] Train's auc: 0.98173 Evaluation's auc: 0.835576 [2155] Train's auc: 0.98174 Evaluation's auc: 0.835595 [2156] Train's auc: 0.981743 Evaluation's auc: 0.835617 [2157] Train's auc: 0.981757 Evaluation's auc: 0.835612 [2158] Train's auc: 0.981782 Evaluation's auc: 0.835611 [2159] Train's auc: 0.981795 Evaluation's auc: 0.83561 [2160] Train's auc: 0.981806 Evaluation's auc: 0.835603 [2161] Train's auc: 0.981812 Evaluation's auc: 0.835603 [2162] Train's auc: 0.981823 Evaluation's auc: 0.835595 [2163] Train's auc: 0.981832 Evaluation's auc: 0.835566 [2164] Train's auc: 0.981833 Evaluation's auc: 0.835561 [2165] Train's auc: 0.981848 Evaluation's auc: 0.835542 [2166] Train's auc: 0.981862 Evaluation's auc: 0.835496 [2167] Train's auc: 0.98187 Evaluation's auc: 0.835473 [2168] Train's auc: 0.981873 Evaluation's auc: 0.835475 [2169] Train's auc: 0.981869 Evaluation's auc: 0.8355 [2170] Train's auc: 0.981882 Evaluation's auc: 0.835496 [2171] Train's auc: 0.981886 Evaluation's auc: 0.835501 [2172] Train's auc: 0.981898 Evaluation's auc: 0.83548 [2173] Train's auc: 0.981911 Evaluation's auc: 0.83543 [2174] Train's auc: 0.981925 Evaluation's auc: 0.835451 [2175] Train's auc: 0.981934 Evaluation's auc: 0.835441 [2176] Train's auc: 0.981941 Evaluation's auc: 0.835416 [2177] Train's auc: 0.981953 Evaluation's auc: 0.835384 [2178] Train's auc: 0.981965 Evaluation's auc: 0.835368 [2179] Train's auc: 0.981988 Evaluation's auc: 0.835381 [2180] Train's auc: 0.981992 Evaluation's auc: 0.835389 [2181] Train's auc: 0.981997 Evaluation's auc: 0.835377 [2182] Train's auc: 0.982008 Evaluation's auc: 0.835395 [2183] Train's auc: 0.982009 Evaluation's auc: 0.835395 [2184] Train's auc: 0.982012 Evaluation's auc: 0.835412 [2185] Train's auc: 0.982012 Evaluation's auc: 0.835425 [2186] Train's auc: 0.982019 Evaluation's auc: 0.835394 [2187] Train's auc: 0.982033 Evaluation's auc: 0.835371 [2188] Train's auc: 0.982042 Evaluation's auc: 0.835352 [2189] Train's auc: 0.982057 Evaluation's auc: 0.835321 [2190] Train's auc: 0.982068 Evaluation's auc: 0.83531 [2191] Train's auc: 0.98208 Evaluation's auc: 0.835291 [2192] Train's auc: 0.982088 Evaluation's auc: 0.835296 [2193] Train's auc: 0.982105 Evaluation's auc: 0.835298 [2194] Train's auc: 0.982114 Evaluation's auc: 0.835284 [2195] Train's auc: 0.982126 Evaluation's auc: 0.835257 [2196] Train's auc: 0.982128 Evaluation's auc: 0.835272 [2197] Train's auc: 0.982134 Evaluation's auc: 0.835271 [2198] Train's auc: 0.982133 Evaluation's auc: 0.835273 [2199] Train's auc: 0.982134 Evaluation's auc: 0.835279 [2200] Train's auc: 0.982138 Evaluation's auc: 0.835337 [2201] Train's auc: 0.982166 Evaluation's auc: 0.835341 [2202] Train's auc: 0.982178 Evaluation's auc: 0.835333 [2203] Train's auc: 0.982186 Evaluation's auc: 0.835323 [2204] Train's auc: 0.982199 Evaluation's auc: 0.835278 [2205] Train's auc: 0.9822 Evaluation's auc: 0.835276 [2206] Train's auc: 0.982208 Evaluation's auc: 0.835296 [2207] Train's auc: 0.982201 Evaluation's auc: 0.835289 [2208] Train's auc: 0.982213 Evaluation's auc: 0.835293 [2209] Train's auc: 0.982231 Evaluation's auc: 0.835254 [2210] Train's auc: 0.982244 Evaluation's auc: 0.835268 [2211] Train's auc: 0.982242 Evaluation's auc: 0.83525 [2212] Train's auc: 0.982261 Evaluation's auc: 0.835242 [2213] Train's auc: 0.982267 Evaluation's auc: 0.835234 [2214] Train's auc: 0.98227 Evaluation's auc: 0.835239 [2215] Train's auc: 0.982277 Evaluation's auc: 0.835213 [2216] Train's auc: 0.982288 Evaluation's auc: 0.835181 [2217] Train's auc: 0.982291 Evaluation's auc: 0.835174 [2218] Train's auc: 0.982298 Evaluation's auc: 0.835185 [2219] Train's auc: 0.982295 Evaluation's auc: 0.835189 [2220] Train's auc: 0.982298 Evaluation's auc: 0.835187 [2221] Train's auc: 0.982307 Evaluation's auc: 0.835201 [2222] Train's auc: 0.982308 Evaluation's auc: 0.8352 [2223] Train's auc: 0.982318 Evaluation's auc: 0.835169 [2224] Train's auc: 0.982328 Evaluation's auc: 0.835152 [2225] Train's auc: 0.982317 Evaluation's auc: 0.835145 [2226] Train's auc: 0.982328 Evaluation's auc: 0.835143 [2227] Train's auc: 0.98234 Evaluation's auc: 0.835131 [2228] Train's auc: 0.982348 Evaluation's auc: 0.835122 [2229] Train's auc: 0.982357 Evaluation's auc: 0.835099 [2230] Train's auc: 0.982359 Evaluation's auc: 0.835094 [2231] Train's auc: 0.98236 Evaluation's auc: 0.835087 [2232] Train's auc: 0.98236 Evaluation's auc: 0.835088 [2233] Train's auc: 0.982366 Evaluation's auc: 0.835068 [2234] Train's auc: 0.982388 Evaluation's auc: 0.83502 [2235] Train's auc: 0.982406 Evaluation's auc: 0.834946 [2236] Train's auc: 0.982422 Evaluation's auc: 0.834942 [2237] Train's auc: 0.982432 Evaluation's auc: 0.834964 [2238] Train's auc: 0.982442 Evaluation's auc: 0.834948 [2239] Train's auc: 0.982467 Evaluation's auc: 0.834933 [2240] Train's auc: 0.982475 Evaluation's auc: 0.834966 [2241] Train's auc: 0.982477 Evaluation's auc: 0.834976 [2242] Train's auc: 0.98249 Evaluation's auc: 0.834994 [2243] Train's auc: 0.982489 Evaluation's auc: 0.835018 [2244] Train's auc: 0.982502 Evaluation's auc: 0.834976 [2245] Train's auc: 0.982506 Evaluation's auc: 0.834967 [2246] Train's auc: 0.982517 Evaluation's auc: 0.834982 [2247] Train's auc: 0.982538 Evaluation's auc: 0.834961 [2248] Train's auc: 0.982537 Evaluation's auc: 0.83497 [2249] Train's auc: 0.98254 Evaluation's auc: 0.834993 [2250] Train's auc: 0.982559 Evaluation's auc: 0.834988 [2251] Train's auc: 0.982572 Evaluation's auc: 0.83499 [2252] Train's auc: 0.982585 Evaluation's auc: 0.834986 [2253] Train's auc: 0.98258 Evaluation's auc: 0.834999 [2254] Train's auc: 0.982584 Evaluation's auc: 0.835025 [2255] Train's auc: 0.98259 Evaluation's auc: 0.835034 [2256] Train's auc: 0.982593 Evaluation's auc: 0.835037 [2257] Train's auc: 0.982604 Evaluation's auc: 0.835005 [2258] Train's auc: 0.982605 Evaluation's auc: 0.834996 [2259] Train's auc: 0.982599 Evaluation's auc: 0.835039 [2260] Train's auc: 0.982606 Evaluation's auc: 0.835038 [2261] Train's auc: 0.98261 Evaluation's auc: 0.835062 [2262] Train's auc: 0.982615 Evaluation's auc: 0.835054 [2263] Train's auc: 0.982627 Evaluation's auc: 0.835056 [2264] Train's auc: 0.982634 Evaluation's auc: 0.835068 [2265] Train's auc: 0.982648 Evaluation's auc: 0.83508 [2266] Train's auc: 0.982662 Evaluation's auc: 0.835078 [2267] Train's auc: 0.982664 Evaluation's auc: 0.835069 [2268] Train's auc: 0.982665 Evaluation's auc: 0.835051 [2269] Train's auc: 0.98268 Evaluation's auc: 0.83506 [2270] Train's auc: 0.982684 Evaluation's auc: 0.83505 [2271] Train's auc: 0.982691 Evaluation's auc: 0.835042 [2272] Train's auc: 0.982699 Evaluation's auc: 0.835042 [2273] Train's auc: 0.982698 Evaluation's auc: 0.835039 [2274] Train's auc: 0.982711 Evaluation's auc: 0.835059 [2275] Train's auc: 0.982713 Evaluation's auc: 0.835063 [2276] Train's auc: 0.982715 Evaluation's auc: 0.83505 [2277] Train's auc: 0.982722 Evaluation's auc: 0.835062 [2278] Train's auc: 0.982734 Evaluation's auc: 0.835056 [2279] Train's auc: 0.982745 Evaluation's auc: 0.835037 [2280] Train's auc: 0.982758 Evaluation's auc: 0.835017 [2281] Train's auc: 0.982759 Evaluation's auc: 0.835006 [2282] Train's auc: 0.98277 Evaluation's auc: 0.835001 [2283] Train's auc: 0.982783 Evaluation's auc: 0.835028 [2284] Train's auc: 0.982802 Evaluation's auc: 0.834986 [2285] Train's auc: 0.98282 Evaluation's auc: 0.834976 [2286] Train's auc: 0.982833 Evaluation's auc: 0.834945 [2287] Train's auc: 0.98285 Evaluation's auc: 0.834934 [2288] Train's auc: 0.982854 Evaluation's auc: 0.834936 [2289] Train's auc: 0.982856 Evaluation's auc: 0.834952 [2290] Train's auc: 0.982859 Evaluation's auc: 0.834948 [2291] Train's auc: 0.982863 Evaluation's auc: 0.834945 [2292] Train's auc: 0.982867 Evaluation's auc: 0.834946 [2293] Train's auc: 0.982884 Evaluation's auc: 0.834915 [2294] Train's auc: 0.982886 Evaluation's auc: 0.834968 [2295] Train's auc: 0.982899 Evaluation's auc: 0.834958 [2296] Train's auc: 0.982907 Evaluation's auc: 0.834967 [2297] Train's auc: 0.982912 Evaluation's auc: 0.834977 [2298] Train's auc: 0.982914 Evaluation's auc: 0.834968 [2299] Train's auc: 0.982916 Evaluation's auc: 0.834953 [2300] Train's auc: 0.982925 Evaluation's auc: 0.834925 [2301] Train's auc: 0.982927 Evaluation's auc: 0.834947 [2302] Train's auc: 0.98293 Evaluation's auc: 0.834958 [2303] Train's auc: 0.982942 Evaluation's auc: 0.834958 [2304] Train's auc: 0.98295 Evaluation's auc: 0.834959 [2305] Train's auc: 0.982964 Evaluation's auc: 0.834944 [2306] Train's auc: 0.982965 Evaluation's auc: 0.834923 [2307] Train's auc: 0.982985 Evaluation's auc: 0.834915 [2308] Train's auc: 0.982999 Evaluation's auc: 0.834924 [2309] Train's auc: 0.983002 Evaluation's auc: 0.834901 [2310] Train's auc: 0.983012 Evaluation's auc: 0.834894 [2311] Train's auc: 0.983021 Evaluation's auc: 0.834886 [2312] Train's auc: 0.983037 Evaluation's auc: 0.834865 [2313] Train's auc: 0.983046 Evaluation's auc: 0.834877 [2314] Train's auc: 0.983057 Evaluation's auc: 0.834861 [2315] Train's auc: 0.983057 Evaluation's auc: 0.834875 [2316] Train's auc: 0.983061 Evaluation's auc: 0.834863 [2317] Train's auc: 0.983076 Evaluation's auc: 0.834852 [2318] Train's auc: 0.983093 Evaluation's auc: 0.834827 [2319] Train's auc: 0.983101 Evaluation's auc: 0.834844 [2320] Train's auc: 0.983116 Evaluation's auc: 0.834864 [2321] Train's auc: 0.98313 Evaluation's auc: 0.834867 [2322] Train's auc: 0.983141 Evaluation's auc: 0.834862 [2323] Train's auc: 0.983151 Evaluation's auc: 0.834863 [2324] Train's auc: 0.983155 Evaluation's auc: 0.83486 [2325] Train's auc: 0.983153 Evaluation's auc: 0.834857 [2326] Train's auc: 0.98316 Evaluation's auc: 0.834847 [2327] Train's auc: 0.98316 Evaluation's auc: 0.834846 [2328] Train's auc: 0.983168 Evaluation's auc: 0.834858 [2329] Train's auc: 0.983173 Evaluation's auc: 0.834837 [2330] Train's auc: 0.983185 Evaluation's auc: 0.834837 [2331] Train's auc: 0.983193 Evaluation's auc: 0.834831 [2332] Train's auc: 0.983215 Evaluation's auc: 0.834833 [2333] Train's auc: 0.983212 Evaluation's auc: 0.834831 [2334] Train's auc: 0.983222 Evaluation's auc: 0.834842 [2335] Train's auc: 0.983226 Evaluation's auc: 0.834829 [2336] Train's auc: 0.98323 Evaluation's auc: 0.834832 [2337] Train's auc: 0.98323 Evaluation's auc: 0.834817 [2338] Train's auc: 0.983242 Evaluation's auc: 0.834824 [2339] Train's auc: 0.983246 Evaluation's auc: 0.834821 [2340] Train's auc: 0.983253 Evaluation's auc: 0.834815 [2341] Train's auc: 0.983254 Evaluation's auc: 0.834814 [2342] Train's auc: 0.983266 Evaluation's auc: 0.834831 [2343] Train's auc: 0.983274 Evaluation's auc: 0.834834 [2344] Train's auc: 0.983273 Evaluation's auc: 0.834835 [2345] Train's auc: 0.983274 Evaluation's auc: 0.834828 [2346] Train's auc: 0.983281 Evaluation's auc: 0.83481 [2347] Train's auc: 0.98329 Evaluation's auc: 0.834789 [2348] Train's auc: 0.983288 Evaluation's auc: 0.834791 [2349] Train's auc: 0.983303 Evaluation's auc: 0.834783 [2350] Train's auc: 0.983301 Evaluation's auc: 0.834784 [2351] Train's auc: 0.983308 Evaluation's auc: 0.834802 [2352] Train's auc: 0.983321 Evaluation's auc: 0.834802 [2353] Train's auc: 0.983332 Evaluation's auc: 0.834797 [2354] Train's auc: 0.983336 Evaluation's auc: 0.834789 [2355] Train's auc: 0.983347 Evaluation's auc: 0.834758 [2356] Train's auc: 0.983351 Evaluation's auc: 0.834753 [2357] Train's auc: 0.983364 Evaluation's auc: 0.834764 [2358] Train's auc: 0.983371 Evaluation's auc: 0.834755 [2359] Train's auc: 0.983379 Evaluation's auc: 0.83476 [2360] Train's auc: 0.983379 Evaluation's auc: 0.834772 [2361] Train's auc: 0.983377 Evaluation's auc: 0.83477 [2362] Train's auc: 0.983378 Evaluation's auc: 0.834768 [2363] Train's auc: 0.983386 Evaluation's auc: 0.83474 [2364] Train's auc: 0.983393 Evaluation's auc: 0.834742 [2365] Train's auc: 0.9834 Evaluation's auc: 0.834766 [2366] Train's auc: 0.983402 Evaluation's auc: 0.834776 [2367] Train's auc: 0.983425 Evaluation's auc: 0.834789 [2368] Train's auc: 0.983432 Evaluation's auc: 0.834797 [2369] Train's auc: 0.983442 Evaluation's auc: 0.834802 [2370] Train's auc: 0.983455 Evaluation's auc: 0.834774 [2371] Train's auc: 0.983455 Evaluation's auc: 0.834777 [2372] Train's auc: 0.983467 Evaluation's auc: 0.834761 [2373] Train's auc: 0.983479 Evaluation's auc: 0.834733 [2374] Train's auc: 0.983479 Evaluation's auc: 0.834722 [2375] Train's auc: 0.983482 Evaluation's auc: 0.834698 [2376] Train's auc: 0.98352 Evaluation's auc: 0.834734 [2377] Train's auc: 0.983535 Evaluation's auc: 0.834755 [2378] Train's auc: 0.983543 Evaluation's auc: 0.834762 [2379] Train's auc: 0.983538 Evaluation's auc: 0.834772 [2380] Train's auc: 0.983543 Evaluation's auc: 0.834763 [2381] Train's auc: 0.983551 Evaluation's auc: 0.834746 [2382] Train's auc: 0.983561 Evaluation's auc: 0.834735 [2383] Train's auc: 0.983566 Evaluation's auc: 0.834693 [2384] Train's auc: 0.98357 Evaluation's auc: 0.834683 [2385] Train's auc: 0.983574 Evaluation's auc: 0.834692 [2386] Train's auc: 0.983586 Evaluation's auc: 0.834694 [2387] Train's auc: 0.983601 Evaluation's auc: 0.834681 [2388] Train's auc: 0.983612 Evaluation's auc: 0.834712 [2389] Train's auc: 0.983616 Evaluation's auc: 0.83469 [2390] Train's auc: 0.98363 Evaluation's auc: 0.834701 [2391] Train's auc: 0.983637 Evaluation's auc: 0.834688 [2392] Train's auc: 0.983625 Evaluation's auc: 0.834708 [2393] Train's auc: 0.983621 Evaluation's auc: 0.8347 [2394] Train's auc: 0.98363 Evaluation's auc: 0.834681 [2395] Train's auc: 0.983642 Evaluation's auc: 0.834681 [2396] Train's auc: 0.983657 Evaluation's auc: 0.834671 [2397] Train's auc: 0.983661 Evaluation's auc: 0.834667 [2398] Train's auc: 0.98367 Evaluation's auc: 0.834633 [2399] Train's auc: 0.983677 Evaluation's auc: 0.834626 [2400] Train's auc: 0.98367 Evaluation's auc: 0.834614 [2401] Train's auc: 0.983683 Evaluation's auc: 0.834626 [2402] Train's auc: 0.98369 Evaluation's auc: 0.834634 [2403] Train's auc: 0.983694 Evaluation's auc: 0.834664 [2404] Train's auc: 0.983704 Evaluation's auc: 0.834663 [2405] Train's auc: 0.983714 Evaluation's auc: 0.834693 [2406] Train's auc: 0.983717 Evaluation's auc: 0.834687 [2407] Train's auc: 0.983722 Evaluation's auc: 0.834675 [2408] Train's auc: 0.983732 Evaluation's auc: 0.834676 [2409] Train's auc: 0.983735 Evaluation's auc: 0.834675 [2410] Train's auc: 0.983743 Evaluation's auc: 0.834662 [2411] Train's auc: 0.983751 Evaluation's auc: 0.834669 [2412] Train's auc: 0.983761 Evaluation's auc: 0.834628 [2413] Train's auc: 0.983771 Evaluation's auc: 0.834636 [2414] Train's auc: 0.983781 Evaluation's auc: 0.834599 [2415] Train's auc: 0.983787 Evaluation's auc: 0.834605 [2416] Train's auc: 0.983789 Evaluation's auc: 0.834611 [2417] Train's auc: 0.983794 Evaluation's auc: 0.834644 [2418] Train's auc: 0.983801 Evaluation's auc: 0.834679 [2419] Train's auc: 0.983806 Evaluation's auc: 0.834698 [2420] Train's auc: 0.983806 Evaluation's auc: 0.834689 [2421] Train's auc: 0.983817 Evaluation's auc: 0.834687 [2422] Train's auc: 0.983821 Evaluation's auc: 0.834681 [2423] Train's auc: 0.983825 Evaluation's auc: 0.834696 [2424] Train's auc: 0.983834 Evaluation's auc: 0.834643 [2425] Train's auc: 0.983826 Evaluation's auc: 0.834643 [2426] Train's auc: 0.983835 Evaluation's auc: 0.834642 [2427] Train's auc: 0.983844 Evaluation's auc: 0.834614 [2428] Train's auc: 0.98386 Evaluation's auc: 0.834594 [2429] Train's auc: 0.983863 Evaluation's auc: 0.834582 [2430] Train's auc: 0.98387 Evaluation's auc: 0.834586 [2431] Train's auc: 0.98388 Evaluation's auc: 0.83461 [2432] Train's auc: 0.983891 Evaluation's auc: 0.834583 [2433] Train's auc: 0.98389 Evaluation's auc: 0.834574 [2434] Train's auc: 0.983896 Evaluation's auc: 0.83456 [2435] Train's auc: 0.983901 Evaluation's auc: 0.8346 [2436] Train's auc: 0.983908 Evaluation's auc: 0.834567 [2437] Train's auc: 0.98393 Evaluation's auc: 0.834546 [2438] Train's auc: 0.98393 Evaluation's auc: 0.834544 [2439] Train's auc: 0.98394 Evaluation's auc: 0.83455 [2440] Train's auc: 0.983956 Evaluation's auc: 0.834537 [2441] Train's auc: 0.983958 Evaluation's auc: 0.834557 [2442] Train's auc: 0.983965 Evaluation's auc: 0.834554 [2443] Train's auc: 0.983973 Evaluation's auc: 0.834527 [2444] Train's auc: 0.983977 Evaluation's auc: 0.83452 [2445] Train's auc: 0.983984 Evaluation's auc: 0.834503 [2446] Train's auc: 0.983988 Evaluation's auc: 0.834498 [2447] Train's auc: 0.983999 Evaluation's auc: 0.834493 [2448] Train's auc: 0.984003 Evaluation's auc: 0.834501 [2449] Train's auc: 0.984013 Evaluation's auc: 0.834498 [2450] Train's auc: 0.984015 Evaluation's auc: 0.834482 [2451] Train's auc: 0.984025 Evaluation's auc: 0.834469 [2452] Train's auc: 0.984035 Evaluation's auc: 0.834486 [2453] Train's auc: 0.984053 Evaluation's auc: 0.834452 [2454] Train's auc: 0.984061 Evaluation's auc: 0.834466 [2455] Train's auc: 0.984061 Evaluation's auc: 0.834489 [2456] Train's auc: 0.984064 Evaluation's auc: 0.834465 [2457] Train's auc: 0.984073 Evaluation's auc: 0.834518 [2458] Train's auc: 0.984079 Evaluation's auc: 0.83456 [2459] Train's auc: 0.984092 Evaluation's auc: 0.834557 [2460] Train's auc: 0.984103 Evaluation's auc: 0.834562 [2461] Train's auc: 0.984105 Evaluation's auc: 0.834558 [2462] Train's auc: 0.98411 Evaluation's auc: 0.834558 [2463] Train's auc: 0.984113 Evaluation's auc: 0.834574 [2464] Train's auc: 0.984122 Evaluation's auc: 0.834578 [2465] Train's auc: 0.984119 Evaluation's auc: 0.834592 [2466] Train's auc: 0.984133 Evaluation's auc: 0.834572 [2467] Train's auc: 0.984139 Evaluation's auc: 0.834563 [2468] Train's auc: 0.984151 Evaluation's auc: 0.834567 [2469] Train's auc: 0.984155 Evaluation's auc: 0.834594 [2470] Train's auc: 0.984162 Evaluation's auc: 0.834594 [2471] Train's auc: 0.984175 Evaluation's auc: 0.834565 [2472] Train's auc: 0.984181 Evaluation's auc: 0.83457 [2473] Train's auc: 0.984189 Evaluation's auc: 0.834556 [2474] Train's auc: 0.984194 Evaluation's auc: 0.834535 [2475] Train's auc: 0.984201 Evaluation's auc: 0.834538 [2476] Train's auc: 0.98421 Evaluation's auc: 0.834535 [2477] Train's auc: 0.984211 Evaluation's auc: 0.834535 [2478] Train's auc: 0.984218 Evaluation's auc: 0.834523 [2479] Train's auc: 0.98423 Evaluation's auc: 0.834493 [2480] Train's auc: 0.984232 Evaluation's auc: 0.834512 [2481] Train's auc: 0.984241 Evaluation's auc: 0.834513 [2482] Train's auc: 0.984245 Evaluation's auc: 0.834502 [2483] Train's auc: 0.984244 Evaluation's auc: 0.834507 [2484] Train's auc: 0.984258 Evaluation's auc: 0.834474 [2485] Train's auc: 0.984261 Evaluation's auc: 0.834502 [2486] Train's auc: 0.984263 Evaluation's auc: 0.834474 [2487] Train's auc: 0.984262 Evaluation's auc: 0.834485 [2488] Train's auc: 0.984271 Evaluation's auc: 0.834496 [2489] Train's auc: 0.984272 Evaluation's auc: 0.834493 [2490] Train's auc: 0.984278 Evaluation's auc: 0.834473 [2491] Train's auc: 0.984282 Evaluation's auc: 0.834462 [2492] Train's auc: 0.984289 Evaluation's auc: 0.834466 [2493] Train's auc: 0.984305 Evaluation's auc: 0.834561 [2494] Train's auc: 0.984309 Evaluation's auc: 0.834569 [2495] Train's auc: 0.984318 Evaluation's auc: 0.834566 [2496] Train's auc: 0.984327 Evaluation's auc: 0.834574 [2497] Train's auc: 0.984333 Evaluation's auc: 0.834548 [2498] Train's auc: 0.984333 Evaluation's auc: 0.834549 [2499] Train's auc: 0.984341 Evaluation's auc: 0.834547 [2500] Train's auc: 0.984348 Evaluation's auc: 0.834527 [2501] Train's auc: 0.984356 Evaluation's auc: 0.834511 [2502] Train's auc: 0.984367 Evaluation's auc: 0.834516 [2503] Train's auc: 0.98437 Evaluation's auc: 0.834502 [2504] Train's auc: 0.984371 Evaluation's auc: 0.834495 [2505] Train's auc: 0.984385 Evaluation's auc: 0.834459 [2506] Train's auc: 0.98439 Evaluation's auc: 0.834463 [2507] Train's auc: 0.984389 Evaluation's auc: 0.834457 [2508] Train's auc: 0.98439 Evaluation's auc: 0.834466 [2509] Train's auc: 0.984402 Evaluation's auc: 0.834474 [2510] Train's auc: 0.984408 Evaluation's auc: 0.834514 [2511] Train's auc: 0.984413 Evaluation's auc: 0.834504 [2512] Train's auc: 0.984418 Evaluation's auc: 0.834508 [2513] Train's auc: 0.984421 Evaluation's auc: 0.834518 [2514] Train's auc: 0.984426 Evaluation's auc: 0.834497 [2515] Train's auc: 0.984433 Evaluation's auc: 0.834489 [2516] Train's auc: 0.984443 Evaluation's auc: 0.834501 [2517] Train's auc: 0.984446 Evaluation's auc: 0.834525 [2518] Train's auc: 0.984454 Evaluation's auc: 0.834497 [2519] Train's auc: 0.984464 Evaluation's auc: 0.8345 [2520] Train's auc: 0.984481 Evaluation's auc: 0.834488 [2521] Train's auc: 0.984487 Evaluation's auc: 0.834489 [2522] Train's auc: 0.984494 Evaluation's auc: 0.834474 [2523] Train's auc: 0.984488 Evaluation's auc: 0.834462 [2524] Train's auc: 0.984495 Evaluation's auc: 0.834458 [2525] Train's auc: 0.984504 Evaluation's auc: 0.834441 [2526] Train's auc: 0.984519 Evaluation's auc: 0.834435 [2527] Train's auc: 0.984528 Evaluation's auc: 0.834449 [2528] Train's auc: 0.984532 Evaluation's auc: 0.834463 [2529] Train's auc: 0.984542 Evaluation's auc: 0.834459 [2530] Train's auc: 0.984545 Evaluation's auc: 0.83444 [2531] Train's auc: 0.984555 Evaluation's auc: 0.834436 [2532] Train's auc: 0.984557 Evaluation's auc: 0.834443 [2533] Train's auc: 0.984563 Evaluation's auc: 0.834446 [2534] Train's auc: 0.984563 Evaluation's auc: 0.834442 [2535] Train's auc: 0.984578 Evaluation's auc: 0.834433 [2536] Train's auc: 0.984584 Evaluation's auc: 0.834433 [2537] Train's auc: 0.984591 Evaluation's auc: 0.834411 [2538] Train's auc: 0.984597 Evaluation's auc: 0.834429 [2539] Train's auc: 0.984598 Evaluation's auc: 0.834424 [2540] Train's auc: 0.984607 Evaluation's auc: 0.834396 [2541] Train's auc: 0.984608 Evaluation's auc: 0.834374 [2542] Train's auc: 0.98462 Evaluation's auc: 0.834362 [2543] Train's auc: 0.98465 Evaluation's auc: 0.834382 [2544] Train's auc: 0.984656 Evaluation's auc: 0.834388 [2545] Train's auc: 0.984669 Evaluation's auc: 0.834399 [2546] Train's auc: 0.984675 Evaluation's auc: 0.8344 [2547] Train's auc: 0.984687 Evaluation's auc: 0.834409 [2548] Train's auc: 0.984688 Evaluation's auc: 0.834437 [2549] Train's auc: 0.984674 Evaluation's auc: 0.834459 [2550] Train's auc: 0.984682 Evaluation's auc: 0.834467 [2551] Train's auc: 0.98469 Evaluation's auc: 0.834468 [2552] Train's auc: 0.984697 Evaluation's auc: 0.834461 [2553] Train's auc: 0.984701 Evaluation's auc: 0.834458 [2554] Train's auc: 0.984718 Evaluation's auc: 0.834444 [2555] Train's auc: 0.984735 Evaluation's auc: 0.83443 [2556] Train's auc: 0.984737 Evaluation's auc: 0.834431 [2557] Train's auc: 0.984752 Evaluation's auc: 0.834442 [2558] Train's auc: 0.984755 Evaluation's auc: 0.834431 [2559] Train's auc: 0.984771 Evaluation's auc: 0.834428 [2560] Train's auc: 0.984781 Evaluation's auc: 0.834434 [2561] Train's auc: 0.98478 Evaluation's auc: 0.834437 [2562] Train's auc: 0.984794 Evaluation's auc: 0.834433 [2563] Train's auc: 0.9848 Evaluation's auc: 0.834428 [2564] Train's auc: 0.984804 Evaluation's auc: 0.834419 [2565] Train's auc: 0.984799 Evaluation's auc: 0.834422 [2566] Train's auc: 0.984812 Evaluation's auc: 0.834398 [2567] Train's auc: 0.984824 Evaluation's auc: 0.834411 [2568] Train's auc: 0.98483 Evaluation's auc: 0.834436 [2569] Train's auc: 0.984832 Evaluation's auc: 0.834414 [2570] Train's auc: 0.984843 Evaluation's auc: 0.834436 [2571] Train's auc: 0.984849 Evaluation's auc: 0.834434 [2572] Train's auc: 0.984851 Evaluation's auc: 0.834442 [2573] Train's auc: 0.984876 Evaluation's auc: 0.834424 [2574] Train's auc: 0.984881 Evaluation's auc: 0.83441 [2575] Train's auc: 0.984877 Evaluation's auc: 0.834451 [2576] Train's auc: 0.984895 Evaluation's auc: 0.834457 [2577] Train's auc: 0.984899 Evaluation's auc: 0.834462 [2578] Train's auc: 0.984904 Evaluation's auc: 0.834441 [2579] Train's auc: 0.984904 Evaluation's auc: 0.834428 [2580] Train's auc: 0.98491 Evaluation's auc: 0.834417 [2581] Train's auc: 0.984917 Evaluation's auc: 0.834425 [2582] Train's auc: 0.98492 Evaluation's auc: 0.834442 [2583] Train's auc: 0.984926 Evaluation's auc: 0.834436 [2584] Train's auc: 0.984927 Evaluation's auc: 0.834435 [2585] Train's auc: 0.984933 Evaluation's auc: 0.834419 [2586] Train's auc: 0.984933 Evaluation's auc: 0.834422 [2587] Train's auc: 0.984939 Evaluation's auc: 0.834424 [2588] Train's auc: 0.984941 Evaluation's auc: 0.834414 [2589] Train's auc: 0.984946 Evaluation's auc: 0.834384 [2590] Train's auc: 0.984951 Evaluation's auc: 0.83441 [2591] Train's auc: 0.984976 Evaluation's auc: 0.834371 [2592] Train's auc: 0.984975 Evaluation's auc: 0.834377 [2593] Train's auc: 0.984981 Evaluation's auc: 0.834365 [2594] Train's auc: 0.984989 Evaluation's auc: 0.834357 [2595] Train's auc: 0.984999 Evaluation's auc: 0.834326 [2596] Train's auc: 0.984999 Evaluation's auc: 0.834328 [2597] Train's auc: 0.985002 Evaluation's auc: 0.834309 [2598] Train's auc: 0.985008 Evaluation's auc: 0.834304 [2599] Train's auc: 0.985012 Evaluation's auc: 0.83429 [2600] Train's auc: 0.985015 Evaluation's auc: 0.834294 [2601] Train's auc: 0.985021 Evaluation's auc: 0.834303 [2602] Train's auc: 0.985026 Evaluation's auc: 0.834308 [2603] Train's auc: 0.985028 Evaluation's auc: 0.834289 [2604] Train's auc: 0.985037 Evaluation's auc: 0.834307 [2605] Train's auc: 0.985043 Evaluation's auc: 0.83428 [2606] Train's auc: 0.985054 Evaluation's auc: 0.834243 [2607] Train's auc: 0.98506 Evaluation's auc: 0.834226 [2608] Train's auc: 0.985064 Evaluation's auc: 0.834216 [2609] Train's auc: 0.98507 Evaluation's auc: 0.834232 [2610] Train's auc: 0.985076 Evaluation's auc: 0.834221 [2611] Train's auc: 0.985081 Evaluation's auc: 0.834224 [2612] Train's auc: 0.985081 Evaluation's auc: 0.834246 [2613] Train's auc: 0.985091 Evaluation's auc: 0.834242 [2614] Train's auc: 0.985103 Evaluation's auc: 0.83424 [2615] Train's auc: 0.98511 Evaluation's auc: 0.834242 [2616] Train's auc: 0.98512 Evaluation's auc: 0.834229 [2617] Train's auc: 0.985136 Evaluation's auc: 0.834245 [2618] Train's auc: 0.985141 Evaluation's auc: 0.834243 [2619] Train's auc: 0.98512 Evaluation's auc: 0.834263 [2620] Train's auc: 0.985127 Evaluation's auc: 0.834246 [2621] Train's auc: 0.98514 Evaluation's auc: 0.83425 [2622] Train's auc: 0.985148 Evaluation's auc: 0.834242 [2623] Train's auc: 0.985149 Evaluation's auc: 0.834234 [2624] Train's auc: 0.985154 Evaluation's auc: 0.834239 [2625] Train's auc: 0.985165 Evaluation's auc: 0.834197 [2626] Train's auc: 0.985157 Evaluation's auc: 0.83425 [2627] Train's auc: 0.985163 Evaluation's auc: 0.834245 [2628] Train's auc: 0.985163 Evaluation's auc: 0.834245 [2629] Train's auc: 0.98517 Evaluation's auc: 0.834258 [2630] Train's auc: 0.98517 Evaluation's auc: 0.834258 [2631] Train's auc: 0.985174 Evaluation's auc: 0.83426 [2632] Train's auc: 0.985183 Evaluation's auc: 0.834243 [2633] Train's auc: 0.985191 Evaluation's auc: 0.834253 [2634] Train's auc: 0.985194 Evaluation's auc: 0.83426 [2635] Train's auc: 0.985201 Evaluation's auc: 0.834265 [2636] Train's auc: 0.985207 Evaluation's auc: 0.834291 [2637] Train's auc: 0.985218 Evaluation's auc: 0.83427 [2638] Train's auc: 0.985218 Evaluation's auc: 0.83427 [2639] Train's auc: 0.985225 Evaluation's auc: 0.83427 [2640] Train's auc: 0.985237 Evaluation's auc: 0.834232 [2641] Train's auc: 0.985239 Evaluation's auc: 0.834226 [2642] Train's auc: 0.985234 Evaluation's auc: 0.83424 [2643] Train's auc: 0.985241 Evaluation's auc: 0.834237 [2644] Train's auc: 0.985247 Evaluation's auc: 0.834252 [2645] Train's auc: 0.985252 Evaluation's auc: 0.83428 [2646] Train's auc: 0.98526 Evaluation's auc: 0.834261 [2647] Train's auc: 0.98528 Evaluation's auc: 0.834242 [2648] Train's auc: 0.985296 Evaluation's auc: 0.83422 [2649] Train's auc: 0.985309 Evaluation's auc: 0.834228 [2650] Train's auc: 0.985313 Evaluation's auc: 0.834216 [2651] Train's auc: 0.985314 Evaluation's auc: 0.834215 [2652] Train's auc: 0.985319 Evaluation's auc: 0.834215 [2653] Train's auc: 0.985319 Evaluation's auc: 0.83421 [2654] Train's auc: 0.985321 Evaluation's auc: 0.834203 [2655] Train's auc: 0.985327 Evaluation's auc: 0.834187 [2656] Train's auc: 0.985334 Evaluation's auc: 0.834191 [2657] Train's auc: 0.98534 Evaluation's auc: 0.83417 [2658] Train's auc: 0.985339 Evaluation's auc: 0.834169 [2659] Train's auc: 0.985343 Evaluation's auc: 0.834166 [2660] Train's auc: 0.985345 Evaluation's auc: 0.83418 [2661] Train's auc: 0.985348 Evaluation's auc: 0.834173 [2662] Train's auc: 0.985343 Evaluation's auc: 0.834191 [2663] Train's auc: 0.985347 Evaluation's auc: 0.834204 [2664] Train's auc: 0.985353 Evaluation's auc: 0.834204 [2665] Train's auc: 0.985359 Evaluation's auc: 0.834202 [2666] Train's auc: 0.98536 Evaluation's auc: 0.834196 [2667] Train's auc: 0.985367 Evaluation's auc: 0.83418 [2668] Train's auc: 0.985364 Evaluation's auc: 0.834157 [2669] Train's auc: 0.985368 Evaluation's auc: 0.834144 [2670] Train's auc: 0.985375 Evaluation's auc: 0.834123 [2671] Train's auc: 0.985384 Evaluation's auc: 0.834101 [2672] Train's auc: 0.985392 Evaluation's auc: 0.83408 [2673] Train's auc: 0.985398 Evaluation's auc: 0.834106 [2674] Train's auc: 0.985395 Evaluation's auc: 0.834082 [2675] Train's auc: 0.985408 Evaluation's auc: 0.834051 [2676] Train's auc: 0.985414 Evaluation's auc: 0.83404 [2677] Train's auc: 0.98542 Evaluation's auc: 0.834033 [2678] Train's auc: 0.985423 Evaluation's auc: 0.83402 [2679] Train's auc: 0.985439 Evaluation's auc: 0.833986 [2680] Train's auc: 0.985441 Evaluation's auc: 0.833976 [2681] Train's auc: 0.985448 Evaluation's auc: 0.833985 [2682] Train's auc: 0.985453 Evaluation's auc: 0.833981 [2683] Train's auc: 0.985457 Evaluation's auc: 0.83397 [2684] Train's auc: 0.985458 Evaluation's auc: 0.833964 [2685] Train's auc: 0.985459 Evaluation's auc: 0.833962 [2686] Train's auc: 0.985462 Evaluation's auc: 0.833954 [2687] Train's auc: 0.985468 Evaluation's auc: 0.833928 [2688] Train's auc: 0.985476 Evaluation's auc: 0.833944 [2689] Train's auc: 0.985481 Evaluation's auc: 0.833918 [2690] Train's auc: 0.985496 Evaluation's auc: 0.833896 [2691] Train's auc: 0.985498 Evaluation's auc: 0.833916 [2692] Train's auc: 0.985512 Evaluation's auc: 0.833896 [2693] Train's auc: 0.985522 Evaluation's auc: 0.833882 [2694] Train's auc: 0.985531 Evaluation's auc: 0.833865 [2695] Train's auc: 0.985533 Evaluation's auc: 0.83389 [2696] Train's auc: 0.985536 Evaluation's auc: 0.833884 [2697] Train's auc: 0.985539 Evaluation's auc: 0.833885 [2698] Train's auc: 0.985542 Evaluation's auc: 0.833867 [2699] Train's auc: 0.985549 Evaluation's auc: 0.833904 [2700] Train's auc: 0.985556 Evaluation's auc: 0.833921 [2701] Train's auc: 0.985564 Evaluation's auc: 0.833967 [2702] Train's auc: 0.985571 Evaluation's auc: 0.833948 [2703] Train's auc: 0.98558 Evaluation's auc: 0.833967 [2704] Train's auc: 0.985591 Evaluation's auc: 0.833978 [2705] Train's auc: 0.985592 Evaluation's auc: 0.833954 [2706] Train's auc: 0.985595 Evaluation's auc: 0.833942 [2707] Train's auc: 0.985604 Evaluation's auc: 0.833953 [2708] Train's auc: 0.985611 Evaluation's auc: 0.833925 [2709] Train's auc: 0.985616 Evaluation's auc: 0.833915 [2710] Train's auc: 0.985624 Evaluation's auc: 0.833906 [2711] Train's auc: 0.985635 Evaluation's auc: 0.833848 [2712] Train's auc: 0.985639 Evaluation's auc: 0.833862 [2713] Train's auc: 0.985644 Evaluation's auc: 0.833834 [2714] Train's auc: 0.985646 Evaluation's auc: 0.833825 [2715] Train's auc: 0.985647 Evaluation's auc: 0.833815 [2716] Train's auc: 0.985649 Evaluation's auc: 0.833793 [2717] Train's auc: 0.985653 Evaluation's auc: 0.833789 [2718] Train's auc: 0.985662 Evaluation's auc: 0.833765 [2719] Train's auc: 0.985664 Evaluation's auc: 0.833753 [2720] Train's auc: 0.985671 Evaluation's auc: 0.833724 [2721] Train's auc: 0.985678 Evaluation's auc: 0.833746 [2722] Train's auc: 0.985681 Evaluation's auc: 0.833751 [2723] Train's auc: 0.985693 Evaluation's auc: 0.833711 [2724] Train's auc: 0.985694 Evaluation's auc: 0.833712 [2725] Train's auc: 0.985694 Evaluation's auc: 0.83371 [2726] Train's auc: 0.985703 Evaluation's auc: 0.8337 [2727] Train's auc: 0.985708 Evaluation's auc: 0.833682 [2728] Train's auc: 0.98571 Evaluation's auc: 0.833681 [2729] Train's auc: 0.985713 Evaluation's auc: 0.83369 [2730] Train's auc: 0.985721 Evaluation's auc: 0.833681 [2731] Train's auc: 0.985722 Evaluation's auc: 0.833691 [2732] Train's auc: 0.985727 Evaluation's auc: 0.833692 [2733] Train's auc: 0.985729 Evaluation's auc: 0.833675 [2734] Train's auc: 0.985731 Evaluation's auc: 0.83367 [2735] Train's auc: 0.98573 Evaluation's auc: 0.833671 [2736] Train's auc: 0.985732 Evaluation's auc: 0.833696 [2737] Train's auc: 0.985741 Evaluation's auc: 0.833673 [2738] Train's auc: 0.985745 Evaluation's auc: 0.833687 [2739] Train's auc: 0.985753 Evaluation's auc: 0.833707 [2740] Train's auc: 0.985757 Evaluation's auc: 0.833706 [2741] Train's auc: 0.985759 Evaluation's auc: 0.833692 [2742] Train's auc: 0.985766 Evaluation's auc: 0.83368 [2743] Train's auc: 0.985752 Evaluation's auc: 0.833702 [2744] Train's auc: 0.985788 Evaluation's auc: 0.833709 [2745] Train's auc: 0.985793 Evaluation's auc: 0.833678 [2746] Train's auc: 0.985798 Evaluation's auc: 0.833669 [2747] Train's auc: 0.985799 Evaluation's auc: 0.833651 [2748] Train's auc: 0.985802 Evaluation's auc: 0.83365 [2749] Train's auc: 0.985807 Evaluation's auc: 0.833652 [2750] Train's auc: 0.985812 Evaluation's auc: 0.83367 [2751] Train's auc: 0.985816 Evaluation's auc: 0.833663 [2752] Train's auc: 0.985817 Evaluation's auc: 0.833657 [2753] Train's auc: 0.985818 Evaluation's auc: 0.833619 [2754] Train's auc: 0.985832 Evaluation's auc: 0.833649 [2755] Train's auc: 0.985838 Evaluation's auc: 0.833618 [2756] Train's auc: 0.985843 Evaluation's auc: 0.833588 [2757] Train's auc: 0.985852 Evaluation's auc: 0.833591 [2758] Train's auc: 0.985859 Evaluation's auc: 0.833577 [2759] Train's auc: 0.985868 Evaluation's auc: 0.833575 [2760] Train's auc: 0.985875 Evaluation's auc: 0.833565 [2761] Train's auc: 0.985887 Evaluation's auc: 0.833572 [2762] Train's auc: 0.985889 Evaluation's auc: 0.833565 [2763] Train's auc: 0.985897 Evaluation's auc: 0.83359 [2764] Train's auc: 0.985905 Evaluation's auc: 0.833579 [2765] Train's auc: 0.985907 Evaluation's auc: 0.833569 [2766] Train's auc: 0.985914 Evaluation's auc: 0.833553 [2767] Train's auc: 0.985912 Evaluation's auc: 0.833553 [2768] Train's auc: 0.985913 Evaluation's auc: 0.833563 [2769] Train's auc: 0.985922 Evaluation's auc: 0.833563 [2770] Train's auc: 0.985923 Evaluation's auc: 0.833555 [2771] Train's auc: 0.985929 Evaluation's auc: 0.83355 [2772] Train's auc: 0.985939 Evaluation's auc: 0.83355 [2773] Train's auc: 0.985936 Evaluation's auc: 0.833551 [2774] Train's auc: 0.985935 Evaluation's auc: 0.833542 [2775] Train's auc: 0.985941 Evaluation's auc: 0.833522 [2776] Train's auc: 0.985944 Evaluation's auc: 0.833528 [2777] Train's auc: 0.985952 Evaluation's auc: 0.833547 [2778] Train's auc: 0.985961 Evaluation's auc: 0.833546 [2779] Train's auc: 0.985964 Evaluation's auc: 0.833547 [2780] Train's auc: 0.985965 Evaluation's auc: 0.833557 [2781] Train's auc: 0.985963 Evaluation's auc: 0.833544 [2782] Train's auc: 0.985967 Evaluation's auc: 0.833541 [2783] Train's auc: 0.985969 Evaluation's auc: 0.833545 [2784] Train's auc: 0.985973 Evaluation's auc: 0.833543 [2785] Train's auc: 0.985978 Evaluation's auc: 0.833515 [2786] Train's auc: 0.985985 Evaluation's auc: 0.833484 [2787] Train's auc: 0.985985 Evaluation's auc: 0.833483 [2788] Train's auc: 0.985999 Evaluation's auc: 0.833483 [2789] Train's auc: 0.986004 Evaluation's auc: 0.833447 [2790] Train's auc: 0.98601 Evaluation's auc: 0.833467 [2791] Train's auc: 0.986012 Evaluation's auc: 0.833481 [2792] Train's auc: 0.986012 Evaluation's auc: 0.83348 [2793] Train's auc: 0.986016 Evaluation's auc: 0.833487 [2794] Train's auc: 0.986019 Evaluation's auc: 0.833479 [2795] Train's auc: 0.986022 Evaluation's auc: 0.833468 [2796] Train's auc: 0.986024 Evaluation's auc: 0.83346 [2797] Train's auc: 0.986028 Evaluation's auc: 0.833453 [2798] Train's auc: 0.986036 Evaluation's auc: 0.833452 [2799] Train's auc: 0.986049 Evaluation's auc: 0.833452 [2800] Train's auc: 0.986056 Evaluation's auc: 0.833434 [2801] Train's auc: 0.986055 Evaluation's auc: 0.833396 [2802] Train's auc: 0.986058 Evaluation's auc: 0.833395 [2803] Train's auc: 0.98606 Evaluation's auc: 0.833374 [2804] Train's auc: 0.986063 Evaluation's auc: 0.833365 [2805] Train's auc: 0.986068 Evaluation's auc: 0.833341 [2806] Train's auc: 0.986073 Evaluation's auc: 0.833287 [2807] Train's auc: 0.986078 Evaluation's auc: 0.833273 [2808] Train's auc: 0.986082 Evaluation's auc: 0.83327 [2809] Train's auc: 0.986087 Evaluation's auc: 0.833305 [2810] Train's auc: 0.986087 Evaluation's auc: 0.833302 [2811] Train's auc: 0.986087 Evaluation's auc: 0.833292 [2812] Train's auc: 0.986087 Evaluation's auc: 0.833263 [2813] Train's auc: 0.986097 Evaluation's auc: 0.833253 [2814] Train's auc: 0.986102 Evaluation's auc: 0.833236 [2815] Train's auc: 0.986106 Evaluation's auc: 0.833268 [2816] Train's auc: 0.986112 Evaluation's auc: 0.833286 [2817] Train's auc: 0.986115 Evaluation's auc: 0.833282 [2818] Train's auc: 0.986116 Evaluation's auc: 0.833274 [2819] Train's auc: 0.986123 Evaluation's auc: 0.833269 [2820] Train's auc: 0.986127 Evaluation's auc: 0.833251 [2821] Train's auc: 0.986132 Evaluation's auc: 0.833238 [2822] Train's auc: 0.986134 Evaluation's auc: 0.833241 [2823] Train's auc: 0.986135 Evaluation's auc: 0.833237 [2824] Train's auc: 0.986138 Evaluation's auc: 0.83324 [2825] Train's auc: 0.986145 Evaluation's auc: 0.83325 [2826] Train's auc: 0.986158 Evaluation's auc: 0.833252 [2827] Train's auc: 0.986164 Evaluation's auc: 0.833267 [2828] Train's auc: 0.986172 Evaluation's auc: 0.833267 [2829] Train's auc: 0.986172 Evaluation's auc: 0.833258 [2830] Train's auc: 0.986174 Evaluation's auc: 0.833254 [2831] Train's auc: 0.986178 Evaluation's auc: 0.833273 [2832] Train's auc: 0.986183 Evaluation's auc: 0.833233 [2833] Train's auc: 0.986189 Evaluation's auc: 0.83321 [2834] Train's auc: 0.986201 Evaluation's auc: 0.833204 [2835] Train's auc: 0.986198 Evaluation's auc: 0.833198 [2836] Train's auc: 0.986204 Evaluation's auc: 0.833202 [2837] Train's auc: 0.986204 Evaluation's auc: 0.833215 [2838] Train's auc: 0.986207 Evaluation's auc: 0.833229 [2839] Train's auc: 0.98621 Evaluation's auc: 0.833209 [2840] Train's auc: 0.98621 Evaluation's auc: 0.833207 [2841] Train's auc: 0.986216 Evaluation's auc: 0.833189 [2842] Train's auc: 0.986217 Evaluation's auc: 0.833189 [2843] Train's auc: 0.986231 Evaluation's auc: 0.833173 [2844] Train's auc: 0.986238 Evaluation's auc: 0.833188 [2845] Train's auc: 0.986238 Evaluation's auc: 0.833171 [2846] Train's auc: 0.98624 Evaluation's auc: 0.833197 [2847] Train's auc: 0.986243 Evaluation's auc: 0.833199 [2848] Train's auc: 0.986244 Evaluation's auc: 0.833202 [2849] Train's auc: 0.986256 Evaluation's auc: 0.833174 [2850] Train's auc: 0.986262 Evaluation's auc: 0.833145 [2851] Train's auc: 0.986276 Evaluation's auc: 0.833105 [2852] Train's auc: 0.986281 Evaluation's auc: 0.833116 [2853] Train's auc: 0.986286 Evaluation's auc: 0.833104 [2854] Train's auc: 0.986289 Evaluation's auc: 0.833111 [2855] Train's auc: 0.986295 Evaluation's auc: 0.833109 [2856] Train's auc: 0.986301 Evaluation's auc: 0.833123 [2857] Train's auc: 0.9863 Evaluation's auc: 0.833118 [2858] Train's auc: 0.986312 Evaluation's auc: 0.833108 [2859] Train's auc: 0.986315 Evaluation's auc: 0.833109 [2860] Train's auc: 0.986325 Evaluation's auc: 0.833136 [2861] Train's auc: 0.986332 Evaluation's auc: 0.833102 [2862] Train's auc: 0.986337 Evaluation's auc: 0.833064 [2863] Train's auc: 0.986339 Evaluation's auc: 0.833064 [2864] Train's auc: 0.986338 Evaluation's auc: 0.833066 [2865] Train's auc: 0.986339 Evaluation's auc: 0.833074 [2866] Train's auc: 0.986331 Evaluation's auc: 0.833079 [2867] Train's auc: 0.98633 Evaluation's auc: 0.833075 [2868] Train's auc: 0.986338 Evaluation's auc: 0.833072 [2869] Train's auc: 0.986343 Evaluation's auc: 0.833071 [2870] Train's auc: 0.986344 Evaluation's auc: 0.833058 [2871] Train's auc: 0.986347 Evaluation's auc: 0.833059 [2872] Train's auc: 0.986348 Evaluation's auc: 0.833051 [2873] Train's auc: 0.986362 Evaluation's auc: 0.833023 [2874] Train's auc: 0.986364 Evaluation's auc: 0.833043 [2875] Train's auc: 0.986366 Evaluation's auc: 0.833047 [2876] Train's auc: 0.986369 Evaluation's auc: 0.833055 [2877] Train's auc: 0.986361 Evaluation's auc: 0.833086 [2878] Train's auc: 0.986364 Evaluation's auc: 0.833079 [2879] Train's auc: 0.986372 Evaluation's auc: 0.833033 [2880] Train's auc: 0.986374 Evaluation's auc: 0.833028 [2881] Train's auc: 0.986388 Evaluation's auc: 0.833058 [2882] Train's auc: 0.986392 Evaluation's auc: 0.833055 [2883] Train's auc: 0.986399 Evaluation's auc: 0.833016 [2884] Train's auc: 0.986405 Evaluation's auc: 0.83302 [2885] Train's auc: 0.986418 Evaluation's auc: 0.83299 [2886] Train's auc: 0.986422 Evaluation's auc: 0.832988 [2887] Train's auc: 0.986422 Evaluation's auc: 0.832987 [2888] Train's auc: 0.98643 Evaluation's auc: 0.832977 [2889] Train's auc: 0.986433 Evaluation's auc: 0.832975 [2890] Train's auc: 0.986439 Evaluation's auc: 0.832996 [2891] Train's auc: 0.986443 Evaluation's auc: 0.832998 [2892] Train's auc: 0.986447 Evaluation's auc: 0.832989 [2893] Train's auc: 0.986455 Evaluation's auc: 0.832953 [2894] Train's auc: 0.986459 Evaluation's auc: 0.832935 [2895] Train's auc: 0.986461 Evaluation's auc: 0.832923 [2896] Train's auc: 0.986466 Evaluation's auc: 0.832939 [2897] Train's auc: 0.986467 Evaluation's auc: 0.832942 [2898] Train's auc: 0.986466 Evaluation's auc: 0.832953 [2899] Train's auc: 0.98647 Evaluation's auc: 0.832955 [2900] Train's auc: 0.98647 Evaluation's auc: 0.832951 [2901] Train's auc: 0.986477 Evaluation's auc: 0.832931 [2902] Train's auc: 0.986478 Evaluation's auc: 0.83293 [2903] Train's auc: 0.986481 Evaluation's auc: 0.832898 [2904] Train's auc: 0.986493 Evaluation's auc: 0.832888 [2905] Train's auc: 0.986497 Evaluation's auc: 0.832892 [2906] Train's auc: 0.986499 Evaluation's auc: 0.832883 [2907] Train's auc: 0.9865 Evaluation's auc: 0.832882 [2908] Train's auc: 0.986503 Evaluation's auc: 0.832887 [2909] Train's auc: 0.986507 Evaluation's auc: 0.832897 [2910] Train's auc: 0.98651 Evaluation's auc: 0.832911 [2911] Train's auc: 0.986513 Evaluation's auc: 0.832934 [2912] Train's auc: 0.986513 Evaluation's auc: 0.832937 [2913] Train's auc: 0.986513 Evaluation's auc: 0.832932 [2914] Train's auc: 0.986514 Evaluation's auc: 0.832937 [2915] Train's auc: 0.986531 Evaluation's auc: 0.83293 [2916] Train's auc: 0.98654 Evaluation's auc: 0.832938 [2917] Train's auc: 0.986552 Evaluation's auc: 0.832928 [2918] Train's auc: 0.986554 Evaluation's auc: 0.832941 [2919] Train's auc: 0.986554 Evaluation's auc: 0.832941 [2920] Train's auc: 0.986555 Evaluation's auc: 0.832939 [2921] Train's auc: 0.986561 Evaluation's auc: 0.832951 [2922] Train's auc: 0.986564 Evaluation's auc: 0.832953 [2923] Train's auc: 0.986565 Evaluation's auc: 0.832937 [2924] Train's auc: 0.986569 Evaluation's auc: 0.832917 [2925] Train's auc: 0.986572 Evaluation's auc: 0.832985 [2926] Train's auc: 0.986581 Evaluation's auc: 0.832996 [2927] Train's auc: 0.986583 Evaluation's auc: 0.83298 [2928] Train's auc: 0.98659 Evaluation's auc: 0.832987 [2929] Train's auc: 0.986593 Evaluation's auc: 0.832999 [2930] Train's auc: 0.986598 Evaluation's auc: 0.833003 [2931] Train's auc: 0.986599 Evaluation's auc: 0.83298 [2932] Train's auc: 0.986601 Evaluation's auc: 0.833008 [2933] Train's auc: 0.986607 Evaluation's auc: 0.833 [2934] Train's auc: 0.986609 Evaluation's auc: 0.832992 [2935] Train's auc: 0.986617 Evaluation's auc: 0.832979 [2936] Train's auc: 0.986622 Evaluation's auc: 0.832984 [2937] Train's auc: 0.986629 Evaluation's auc: 0.832967 [2938] Train's auc: 0.98663 Evaluation's auc: 0.832972 [2939] Train's auc: 0.986637 Evaluation's auc: 0.832953 [2940] Train's auc: 0.986645 Evaluation's auc: 0.832935 [2941] Train's auc: 0.986662 Evaluation's auc: 0.832937 [2942] Train's auc: 0.986667 Evaluation's auc: 0.832948 [2943] Train's auc: 0.986668 Evaluation's auc: 0.832927 [2944] Train's auc: 0.986667 Evaluation's auc: 0.832934 [2945] Train's auc: 0.986668 Evaluation's auc: 0.832949 [2946] Train's auc: 0.986674 Evaluation's auc: 0.832967 [2947] Train's auc: 0.986679 Evaluation's auc: 0.832963 [2948] Train's auc: 0.986687 Evaluation's auc: 0.832977 [2949] Train's auc: 0.986687 Evaluation's auc: 0.832965 [2950] Train's auc: 0.986689 Evaluation's auc: 0.832962 [2951] Train's auc: 0.986691 Evaluation's auc: 0.832958 [2952] Train's auc: 0.986693 Evaluation's auc: 0.832967 [2953] Train's auc: 0.986694 Evaluation's auc: 0.832992 [2954] Train's auc: 0.986697 Evaluation's auc: 0.833002 [2955] Train's auc: 0.986711 Evaluation's auc: 0.833006 [2956] Train's auc: 0.986718 Evaluation's auc: 0.833002 [2957] Train's auc: 0.986717 Evaluation's auc: 0.833004 [2958] Train's auc: 0.98672 Evaluation's auc: 0.832998 [2959] Train's auc: 0.986725 Evaluation's auc: 0.833001 [2960] Train's auc: 0.986732 Evaluation's auc: 0.832978 [2961] Train's auc: 0.986741 Evaluation's auc: 0.832975 [2962] Train's auc: 0.986744 Evaluation's auc: 0.833013 [2963] Train's auc: 0.986739 Evaluation's auc: 0.833004 [2964] Train's auc: 0.986745 Evaluation's auc: 0.833007 [2965] Train's auc: 0.986746 Evaluation's auc: 0.833016 [2966] Train's auc: 0.986752 Evaluation's auc: 0.833014 [2967] Train's auc: 0.986755 Evaluation's auc: 0.833006 [2968] Train's auc: 0.986755 Evaluation's auc: 0.833002 [2969] Train's auc: 0.98676 Evaluation's auc: 0.833037 [2970] Train's auc: 0.986765 Evaluation's auc: 0.833046 [2971] Train's auc: 0.986767 Evaluation's auc: 0.833047 [2972] Train's auc: 0.986767 Evaluation's auc: 0.833046 [2973] Train's auc: 0.986775 Evaluation's auc: 0.833048 [2974] Train's auc: 0.986777 Evaluation's auc: 0.833063 [2975] Train's auc: 0.986782 Evaluation's auc: 0.833061 [2976] Train's auc: 0.986787 Evaluation's auc: 0.833066 [2977] Train's auc: 0.986795 Evaluation's auc: 0.833047 [2978] Train's auc: 0.986811 Evaluation's auc: 0.83306 [2979] Train's auc: 0.986812 Evaluation's auc: 0.833069 [2980] Train's auc: 0.986816 Evaluation's auc: 0.833061 [2981] Train's auc: 0.986823 Evaluation's auc: 0.833008 [2982] Train's auc: 0.986827 Evaluation's auc: 0.833005 [2983] Train's auc: 0.986827 Evaluation's auc: 0.833014 [2984] Train's auc: 0.986834 Evaluation's auc: 0.832991 [2985] Train's auc: 0.986839 Evaluation's auc: 0.832988 [2986] Train's auc: 0.98684 Evaluation's auc: 0.832981 [2987] Train's auc: 0.986844 Evaluation's auc: 0.832977 [2988] Train's auc: 0.986844 Evaluation's auc: 0.832961 [2989] Train's auc: 0.986849 Evaluation's auc: 0.832962 [2990] Train's auc: 0.986851 Evaluation's auc: 0.832961 [2991] Train's auc: 0.986854 Evaluation's auc: 0.832968 [2992] Train's auc: 0.986862 Evaluation's auc: 0.832952 [2993] Train's auc: 0.986868 Evaluation's auc: 0.832989 [2994] Train's auc: 0.986873 Evaluation's auc: 0.832972 [2995] Train's auc: 0.986874 Evaluation's auc: 0.832965 [2996] Train's auc: 0.986876 Evaluation's auc: 0.832961 [2997] Train's auc: 0.986876 Evaluation's auc: 0.832966 [2998] Train's auc: 0.986877 Evaluation's auc: 0.83296 [2999] Train's auc: 0.986879 Evaluation's auc: 0.832971 [3000] Train's auc: 0.98689 Evaluation's auc: 0.832971 [3001] Train's auc: 0.986893 Evaluation's auc: 0.832962 [3002] Train's auc: 0.986902 Evaluation's auc: 0.832964 [3003] Train's auc: 0.986903 Evaluation's auc: 0.832979 [3004] Train's auc: 0.986909 Evaluation's auc: 0.833014 [3005] Train's auc: 0.986915 Evaluation's auc: 0.832987 [3006] Train's auc: 0.986923 Evaluation's auc: 0.832971 [3007] Train's auc: 0.986925 Evaluation's auc: 0.832974 [3008] Train's auc: 0.986928 Evaluation's auc: 0.832989 [3009] Train's auc: 0.986927 Evaluation's auc: 0.832991 [3010] Train's auc: 0.986929 Evaluation's auc: 0.832994 [3011] Train's auc: 0.986934 Evaluation's auc: 0.832994 [3012] Train's auc: 0.986936 Evaluation's auc: 0.832972 [3013] Train's auc: 0.986941 Evaluation's auc: 0.832984 [3014] Train's auc: 0.986946 Evaluation's auc: 0.832967 [3015] Train's auc: 0.986948 Evaluation's auc: 0.832973 [3016] Train's auc: 0.986961 Evaluation's auc: 0.832964 [3017] Train's auc: 0.986956 Evaluation's auc: 0.832944 [3018] Train's auc: 0.986964 Evaluation's auc: 0.832941 [3019] Train's auc: 0.986968 Evaluation's auc: 0.832924 [3020] Train's auc: 0.986972 Evaluation's auc: 0.832916 [3021] Train's auc: 0.986972 Evaluation's auc: 0.832912 [3022] Train's auc: 0.98698 Evaluation's auc: 0.832914 [3023] Train's auc: 0.986991 Evaluation's auc: 0.832877 [3024] Train's auc: 0.986992 Evaluation's auc: 0.832877 [3025] Train's auc: 0.986993 Evaluation's auc: 0.832871 [3026] Train's auc: 0.986994 Evaluation's auc: 0.832866 [3027] Train's auc: 0.987003 Evaluation's auc: 0.832831 [3028] Train's auc: 0.987006 Evaluation's auc: 0.832805 [3029] Train's auc: 0.987009 Evaluation's auc: 0.832804 [3030] Train's auc: 0.987009 Evaluation's auc: 0.832799 [3031] Train's auc: 0.987013 Evaluation's auc: 0.832806 [3032] Train's auc: 0.987011 Evaluation's auc: 0.832806 [3033] Train's auc: 0.987011 Evaluation's auc: 0.832804 [3034] Train's auc: 0.987014 Evaluation's auc: 0.83279 [3035] Train's auc: 0.987019 Evaluation's auc: 0.832795 [3036] Train's auc: 0.98703 Evaluation's auc: 0.832802 [3037] Train's auc: 0.987031 Evaluation's auc: 0.832787 [3038] Train's auc: 0.987034 Evaluation's auc: 0.832789 [3039] Train's auc: 0.987041 Evaluation's auc: 0.83278 [3040] Train's auc: 0.987042 Evaluation's auc: 0.832796 [3041] Train's auc: 0.987045 Evaluation's auc: 0.8328 [3042] Train's auc: 0.987038 Evaluation's auc: 0.832825 [3043] Train's auc: 0.987041 Evaluation's auc: 0.832828 [3044] Train's auc: 0.987047 Evaluation's auc: 0.832823 [3045] Train's auc: 0.987054 Evaluation's auc: 0.832846 [3046] Train's auc: 0.987048 Evaluation's auc: 0.832872 [3047] Train's auc: 0.98705 Evaluation's auc: 0.832869 [3048] Train's auc: 0.987052 Evaluation's auc: 0.832879 [3049] Train's auc: 0.987062 Evaluation's auc: 0.832872 [3050] Train's auc: 0.987063 Evaluation's auc: 0.832859 [3051] Train's auc: 0.987068 Evaluation's auc: 0.832867 [3052] Train's auc: 0.987075 Evaluation's auc: 0.832884 [3053] Train's auc: 0.987078 Evaluation's auc: 0.832889 [3054] Train's auc: 0.987079 Evaluation's auc: 0.832897 [3055] Train's auc: 0.987079 Evaluation's auc: 0.832897 [3056] Train's auc: 0.987085 Evaluation's auc: 0.832882 [3057] Train's auc: 0.987088 Evaluation's auc: 0.832865 [3058] Train's auc: 0.987094 Evaluation's auc: 0.832857 [3059] Train's auc: 0.987096 Evaluation's auc: 0.83286 [3060] Train's auc: 0.987103 Evaluation's auc: 0.832839 [3061] Train's auc: 0.9871 Evaluation's auc: 0.832834 [3062] Train's auc: 0.987105 Evaluation's auc: 0.832827 [3063] Train's auc: 0.98711 Evaluation's auc: 0.832838 [3064] Train's auc: 0.98711 Evaluation's auc: 0.832837 [3065] Train's auc: 0.987112 Evaluation's auc: 0.832832 [3066] Train's auc: 0.987123 Evaluation's auc: 0.832841 [3067] Train's auc: 0.987129 Evaluation's auc: 0.832869 [3068] Train's auc: 0.987129 Evaluation's auc: 0.832864 [3069] Train's auc: 0.987136 Evaluation's auc: 0.83286 [3070] Train's auc: 0.987145 Evaluation's auc: 0.832854 [3071] Train's auc: 0.987152 Evaluation's auc: 0.832854 [3072] Train's auc: 0.987156 Evaluation's auc: 0.832857 [3073] Train's auc: 0.987162 Evaluation's auc: 0.832855 [3074] Train's auc: 0.98716 Evaluation's auc: 0.832838 [3075] Train's auc: 0.987166 Evaluation's auc: 0.832823 [3076] Train's auc: 0.987167 Evaluation's auc: 0.832832 [3077] Train's auc: 0.987167 Evaluation's auc: 0.832832 [3078] Train's auc: 0.987172 Evaluation's auc: 0.832849 [3079] Train's auc: 0.98717 Evaluation's auc: 0.832873 [3080] Train's auc: 0.987177 Evaluation's auc: 0.83288 [3081] Train's auc: 0.987179 Evaluation's auc: 0.832872 [3082] Train's auc: 0.987188 Evaluation's auc: 0.832849 [3083] Train's auc: 0.987191 Evaluation's auc: 0.832855 [3084] Train's auc: 0.987199 Evaluation's auc: 0.832837 [3085] Train's auc: 0.987201 Evaluation's auc: 0.832852 [3086] Train's auc: 0.987204 Evaluation's auc: 0.832856 [3087] Train's auc: 0.987207 Evaluation's auc: 0.832886 [3088] Train's auc: 0.987212 Evaluation's auc: 0.832869 [3089] Train's auc: 0.987217 Evaluation's auc: 0.832865 [3090] Train's auc: 0.987221 Evaluation's auc: 0.832857 [3091] Train's auc: 0.987224 Evaluation's auc: 0.832846 [3092] Train's auc: 0.987226 Evaluation's auc: 0.832843 [3093] Train's auc: 0.987228 Evaluation's auc: 0.832835 [3094] Train's auc: 0.987232 Evaluation's auc: 0.832835 [3095] Train's auc: 0.987233 Evaluation's auc: 0.832836 [3096] Train's auc: 0.987233 Evaluation's auc: 0.832806 [3097] Train's auc: 0.987239 Evaluation's auc: 0.832826 [3098] Train's auc: 0.987239 Evaluation's auc: 0.832828 [3099] Train's auc: 0.987241 Evaluation's auc: 0.832815 [3100] Train's auc: 0.987243 Evaluation's auc: 0.832813 [3101] Train's auc: 0.987247 Evaluation's auc: 0.832793 [3102] Train's auc: 0.987254 Evaluation's auc: 0.832805 [3103] Train's auc: 0.987257 Evaluation's auc: 0.832799 [3104] Train's auc: 0.987268 Evaluation's auc: 0.832786 [3105] Train's auc: 0.987285 Evaluation's auc: 0.832772 [3106] Train's auc: 0.987287 Evaluation's auc: 0.832763 [3107] Train's auc: 0.987288 Evaluation's auc: 0.832772 [3108] Train's auc: 0.987291 Evaluation's auc: 0.83278 [3109] Train's auc: 0.987284 Evaluation's auc: 0.832804 [3110] Train's auc: 0.987286 Evaluation's auc: 0.832846 [3111] Train's auc: 0.987289 Evaluation's auc: 0.832826 [3112] Train's auc: 0.987297 Evaluation's auc: 0.832839 [3113] Train's auc: 0.9873 Evaluation's auc: 0.832841 [3114] Train's auc: 0.98731 Evaluation's auc: 0.832856 [3115] Train's auc: 0.987313 Evaluation's auc: 0.832876 [3116] Train's auc: 0.987324 Evaluation's auc: 0.832875 [3117] Train's auc: 0.987329 Evaluation's auc: 0.832863 [3118] Train's auc: 0.987329 Evaluation's auc: 0.83285 [3119] Train's auc: 0.987333 Evaluation's auc: 0.832848 [3120] Train's auc: 0.987336 Evaluation's auc: 0.832845 [3121] Train's auc: 0.98734 Evaluation's auc: 0.832823 [3122] Train's auc: 0.987349 Evaluation's auc: 0.832782 [3123] Train's auc: 0.98735 Evaluation's auc: 0.832779 [3124] Train's auc: 0.987359 Evaluation's auc: 0.83275 [3125] Train's auc: 0.987362 Evaluation's auc: 0.832746 [3126] Train's auc: 0.987368 Evaluation's auc: 0.832733 [3127] Train's auc: 0.987373 Evaluation's auc: 0.832743 [3128] Train's auc: 0.987375 Evaluation's auc: 0.832744 [3129] Train's auc: 0.987377 Evaluation's auc: 0.832734 [3130] Train's auc: 0.98738 Evaluation's auc: 0.832728 [3131] Train's auc: 0.987387 Evaluation's auc: 0.832687 [3132] Train's auc: 0.987392 Evaluation's auc: 0.832709 [3133] Train's auc: 0.987393 Evaluation's auc: 0.832707 [3134] Train's auc: 0.987393 Evaluation's auc: 0.832693 [3135] Train's auc: 0.9874 Evaluation's auc: 0.832695 [3136] Train's auc: 0.987408 Evaluation's auc: 0.8327 [3137] Train's auc: 0.987411 Evaluation's auc: 0.832679 [3138] Train's auc: 0.987423 Evaluation's auc: 0.832666 [3139] Train's auc: 0.98743 Evaluation's auc: 0.832668 [3140] Train's auc: 0.987435 Evaluation's auc: 0.832685 [3141] Train's auc: 0.987425 Evaluation's auc: 0.832692 [3142] Train's auc: 0.987434 Evaluation's auc: 0.832691 [3143] Train's auc: 0.987435 Evaluation's auc: 0.832676 [3144] Train's auc: 0.987442 Evaluation's auc: 0.832657 [3145] Train's auc: 0.987448 Evaluation's auc: 0.832654 [3146] Train's auc: 0.987454 Evaluation's auc: 0.832633 [3147] Train's auc: 0.98745 Evaluation's auc: 0.832629 [3148] Train's auc: 0.987467 Evaluation's auc: 0.832622 [3149] Train's auc: 0.987464 Evaluation's auc: 0.832622 [3150] Train's auc: 0.987461 Evaluation's auc: 0.832619 [3151] Train's auc: 0.987461 Evaluation's auc: 0.832612 [3152] Train's auc: 0.987468 Evaluation's auc: 0.8326 [3153] Train's auc: 0.987473 Evaluation's auc: 0.832598 [3154] Train's auc: 0.987476 Evaluation's auc: 0.832605 [3155] Train's auc: 0.987479 Evaluation's auc: 0.832595 [3156] Train's auc: 0.987473 Evaluation's auc: 0.832604 [3157] Train's auc: 0.987479 Evaluation's auc: 0.832587 [3158] Train's auc: 0.987479 Evaluation's auc: 0.832594 [3159] Train's auc: 0.987475 Evaluation's auc: 0.832576 [3160] Train's auc: 0.987481 Evaluation's auc: 0.832549 [3161] Train's auc: 0.987489 Evaluation's auc: 0.832524 [3162] Train's auc: 0.987488 Evaluation's auc: 0.832511 [3163] Train's auc: 0.987493 Evaluation's auc: 0.832506 [3164] Train's auc: 0.987497 Evaluation's auc: 0.83249 [3165] Train's auc: 0.987512 Evaluation's auc: 0.832497 [3166] Train's auc: 0.987517 Evaluation's auc: 0.832475 [3167] Train's auc: 0.98752 Evaluation's auc: 0.832472 [3168] Train's auc: 0.987518 Evaluation's auc: 0.832475 [3169] Train's auc: 0.987517 Evaluation's auc: 0.832463 [3170] Train's auc: 0.987522 Evaluation's auc: 0.832477 [3171] Train's auc: 0.987525 Evaluation's auc: 0.832478 [3172] Train's auc: 0.987524 Evaluation's auc: 0.832481 [3173] Train's auc: 0.987526 Evaluation's auc: 0.832451 [3174] Train's auc: 0.987527 Evaluation's auc: 0.832456 [3175] Train's auc: 0.987523 Evaluation's auc: 0.832457 [3176] Train's auc: 0.987526 Evaluation's auc: 0.832459 [3177] Train's auc: 0.987534 Evaluation's auc: 0.832433 [3178] Train's auc: 0.987536 Evaluation's auc: 0.832448 [3179] Train's auc: 0.987535 Evaluation's auc: 0.832446 [3180] Train's auc: 0.987533 Evaluation's auc: 0.832461 [3181] Train's auc: 0.987535 Evaluation's auc: 0.832459 [3182] Train's auc: 0.987547 Evaluation's auc: 0.832458 [3183] Train's auc: 0.98756 Evaluation's auc: 0.832456 [3184] Train's auc: 0.987563 Evaluation's auc: 0.832492 [3185] Train's auc: 0.987564 Evaluation's auc: 0.832492 [3186] Train's auc: 0.98757 Evaluation's auc: 0.832487 [3187] Train's auc: 0.987566 Evaluation's auc: 0.832543 [3188] Train's auc: 0.987572 Evaluation's auc: 0.832541 [3189] Train's auc: 0.987575 Evaluation's auc: 0.832534 [3190] Train's auc: 0.987578 Evaluation's auc: 0.832509 [3191] Train's auc: 0.987584 Evaluation's auc: 0.832486 [3192] Train's auc: 0.987589 Evaluation's auc: 0.832504 [3193] Train's auc: 0.987587 Evaluation's auc: 0.832502 [3194] Train's auc: 0.987594 Evaluation's auc: 0.832472 [3195] Train's auc: 0.987598 Evaluation's auc: 0.832482 [3196] Train's auc: 0.987606 Evaluation's auc: 0.832482 [3197] Train's auc: 0.98761 Evaluation's auc: 0.832471 [3198] Train's auc: 0.987614 Evaluation's auc: 0.832468 [3199] Train's auc: 0.987616 Evaluation's auc: 0.832447 [3200] Train's auc: 0.987615 Evaluation's auc: 0.832445 [3201] Train's auc: 0.98762 Evaluation's auc: 0.832458 [3202] Train's auc: 0.987624 Evaluation's auc: 0.832444 [3203] Train's auc: 0.98763 Evaluation's auc: 0.832424 [3204] Train's auc: 0.98763 Evaluation's auc: 0.832439 [3205] Train's auc: 0.987633 Evaluation's auc: 0.832467 [3206] Train's auc: 0.987632 Evaluation's auc: 0.832457 [3207] Train's auc: 0.987637 Evaluation's auc: 0.832421 [3208] Train's auc: 0.987636 Evaluation's auc: 0.832431 [3209] Train's auc: 0.987636 Evaluation's auc: 0.832426 [3210] Train's auc: 0.98764 Evaluation's auc: 0.832429 [3211] Train's auc: 0.98765 Evaluation's auc: 0.83241 [3212] Train's auc: 0.987652 Evaluation's auc: 0.832433 [3213] Train's auc: 0.987658 Evaluation's auc: 0.832413 [3214] Train's auc: 0.987659 Evaluation's auc: 0.832431 [3215] Train's auc: 0.987655 Evaluation's auc: 0.832437 [3216] Train's auc: 0.987658 Evaluation's auc: 0.832424 [3217] Train's auc: 0.987662 Evaluation's auc: 0.832411 [3218] Train's auc: 0.987666 Evaluation's auc: 0.832416 [3219] Train's auc: 0.987667 Evaluation's auc: 0.832422 [3220] Train's auc: 0.987669 Evaluation's auc: 0.832454 [3221] Train's auc: 0.987672 Evaluation's auc: 0.832456 [3222] Train's auc: 0.987677 Evaluation's auc: 0.832449 [3223] Train's auc: 0.987682 Evaluation's auc: 0.83243 [3224] Train's auc: 0.987686 Evaluation's auc: 0.832462 [3225] Train's auc: 0.987704 Evaluation's auc: 0.832455 [3226] Train's auc: 0.987707 Evaluation's auc: 0.832467 [3227] Train's auc: 0.987711 Evaluation's auc: 0.832446 [3228] Train's auc: 0.987715 Evaluation's auc: 0.832447 [3229] Train's auc: 0.987718 Evaluation's auc: 0.83245 [3230] Train's auc: 0.987722 Evaluation's auc: 0.832425 [3231] Train's auc: 0.987726 Evaluation's auc: 0.832443 [3232] Train's auc: 0.98773 Evaluation's auc: 0.832432 [3233] Train's auc: 0.98773 Evaluation's auc: 0.832434 [3234] Train's auc: 0.987723 Evaluation's auc: 0.832431 [3235] Train's auc: 0.987725 Evaluation's auc: 0.832431 [3236] Train's auc: 0.987736 Evaluation's auc: 0.832431 [3237] Train's auc: 0.987737 Evaluation's auc: 0.832425 [3238] Train's auc: 0.987736 Evaluation's auc: 0.832423 [3239] Train's auc: 0.987741 Evaluation's auc: 0.832426 [3240] Train's auc: 0.987741 Evaluation's auc: 0.83242 [3241] Train's auc: 0.987747 Evaluation's auc: 0.832441 [3242] Train's auc: 0.987747 Evaluation's auc: 0.832447 [3243] Train's auc: 0.987746 Evaluation's auc: 0.832451 [3244] Train's auc: 0.987758 Evaluation's auc: 0.832437 [3245] Train's auc: 0.987752 Evaluation's auc: 0.832437 [3246] Train's auc: 0.987757 Evaluation's auc: 0.832435 [3247] Train's auc: 0.987763 Evaluation's auc: 0.83242 [3248] Train's auc: 0.987763 Evaluation's auc: 0.832423 [3249] Train's auc: 0.98777 Evaluation's auc: 0.832427 [3250] Train's auc: 0.987779 Evaluation's auc: 0.832429 [3251] Train's auc: 0.98778 Evaluation's auc: 0.832438 [3252] Train's auc: 0.987786 Evaluation's auc: 0.832454 [3253] Train's auc: 0.987791 Evaluation's auc: 0.832422 [3254] Train's auc: 0.987792 Evaluation's auc: 0.832435 [3255] Train's auc: 0.987797 Evaluation's auc: 0.83244 [3256] Train's auc: 0.987804 Evaluation's auc: 0.832428 [3257] Train's auc: 0.987806 Evaluation's auc: 0.832424 [3258] Train's auc: 0.987808 Evaluation's auc: 0.832417 [3259] Train's auc: 0.987817 Evaluation's auc: 0.832399 [3260] Train's auc: 0.987819 Evaluation's auc: 0.832392 [3261] Train's auc: 0.987825 Evaluation's auc: 0.832366 [3262] Train's auc: 0.987838 Evaluation's auc: 0.832365 [3263] Train's auc: 0.987839 Evaluation's auc: 0.832359 [3264] Train's auc: 0.987842 Evaluation's auc: 0.832376 [3265] Train's auc: 0.987856 Evaluation's auc: 0.832368 [3266] Train's auc: 0.987853 Evaluation's auc: 0.832378 [3267] Train's auc: 0.987856 Evaluation's auc: 0.832383 [3268] Train's auc: 0.987874 Evaluation's auc: 0.832405 [3269] Train's auc: 0.987892 Evaluation's auc: 0.832376 [3270] Train's auc: 0.987897 Evaluation's auc: 0.832365 [3271] Train's auc: 0.987901 Evaluation's auc: 0.832338 [3272] Train's auc: 0.987901 Evaluation's auc: 0.832314 [3273] Train's auc: 0.987903 Evaluation's auc: 0.832305 [3274] Train's auc: 0.987903 Evaluation's auc: 0.832305 [3275] Train's auc: 0.987908 Evaluation's auc: 0.832292 [3276] Train's auc: 0.987913 Evaluation's auc: 0.832293 [3277] Train's auc: 0.987913 Evaluation's auc: 0.832298 [3278] Train's auc: 0.987918 Evaluation's auc: 0.832292 [3279] Train's auc: 0.987921 Evaluation's auc: 0.832313 [3280] Train's auc: 0.987926 Evaluation's auc: 0.832342 [3281] Train's auc: 0.987927 Evaluation's auc: 0.83234 [3282] Train's auc: 0.987924 Evaluation's auc: 0.832354 [3283] Train's auc: 0.987925 Evaluation's auc: 0.83235 [3284] Train's auc: 0.987922 Evaluation's auc: 0.832351 [3285] Train's auc: 0.987928 Evaluation's auc: 0.832352 [3286] Train's auc: 0.987929 Evaluation's auc: 0.832357 [3287] Train's auc: 0.987934 Evaluation's auc: 0.832379 [3288] Train's auc: 0.987942 Evaluation's auc: 0.83237 [3289] Train's auc: 0.987947 Evaluation's auc: 0.832365 [3290] Train's auc: 0.987947 Evaluation's auc: 0.832367 [3291] Train's auc: 0.98795 Evaluation's auc: 0.832376 [3292] Train's auc: 0.987957 Evaluation's auc: 0.83236 [3293] Train's auc: 0.987958 Evaluation's auc: 0.832352 [3294] Train's auc: 0.987961 Evaluation's auc: 0.832358 [3295] Train's auc: 0.98797 Evaluation's auc: 0.832332 [3296] Train's auc: 0.98797 Evaluation's auc: 0.83233 [3297] Train's auc: 0.98797 Evaluation's auc: 0.832346 [3298] Train's auc: 0.987974 Evaluation's auc: 0.832323 [3299] Train's auc: 0.98797 Evaluation's auc: 0.832303 [3300] Train's auc: 0.987976 Evaluation's auc: 0.832289 [3301] Train's auc: 0.987979 Evaluation's auc: 0.832302 [3302] Train's auc: 0.987988 Evaluation's auc: 0.832279 [3303] Train's auc: 0.987992 Evaluation's auc: 0.832293 [3304] Train's auc: 0.987982 Evaluation's auc: 0.832297 [3305] Train's auc: 0.987987 Evaluation's auc: 0.832307 [3306] Train's auc: 0.987993 Evaluation's auc: 0.832312 [3307] Train's auc: 0.987993 Evaluation's auc: 0.832316 [3308] Train's auc: 0.987999 Evaluation's auc: 0.832338 [3309] Train's auc: 0.988002 Evaluation's auc: 0.832328 [3310] Train's auc: 0.988006 Evaluation's auc: 0.832327 [3311] Train's auc: 0.98801 Evaluation's auc: 0.832313 [3312] Train's auc: 0.988012 Evaluation's auc: 0.832325 [3313] Train's auc: 0.988013 Evaluation's auc: 0.832309 [3314] Train's auc: 0.988014 Evaluation's auc: 0.832311 [3315] Train's auc: 0.987999 Evaluation's auc: 0.832309 [3316] Train's auc: 0.988005 Evaluation's auc: 0.832303 [3317] Train's auc: 0.988007 Evaluation's auc: 0.832302 [3318] Train's auc: 0.988009 Evaluation's auc: 0.832288 [3319] Train's auc: 0.988027 Evaluation's auc: 0.832295 [3320] Train's auc: 0.988037 Evaluation's auc: 0.83228 [3321] Train's auc: 0.988052 Evaluation's auc: 0.832274 [3322] Train's auc: 0.988056 Evaluation's auc: 0.832281 [3323] Train's auc: 0.988059 Evaluation's auc: 0.832287 [3324] Train's auc: 0.988059 Evaluation's auc: 0.832288 [3325] Train's auc: 0.988066 Evaluation's auc: 0.832258 [3326] Train's auc: 0.988069 Evaluation's auc: 0.832248 [3327] Train's auc: 0.988069 Evaluation's auc: 0.832279 [3328] Train's auc: 0.988074 Evaluation's auc: 0.832261 [3329] Train's auc: 0.988078 Evaluation's auc: 0.832262 [3330] Train's auc: 0.988077 Evaluation's auc: 0.832254 [3331] Train's auc: 0.988079 Evaluation's auc: 0.832272 [3332] Train's auc: 0.988083 Evaluation's auc: 0.83227 [3333] Train's auc: 0.98808 Evaluation's auc: 0.832253 [3334] Train's auc: 0.988083 Evaluation's auc: 0.832254 [3335] Train's auc: 0.988084 Evaluation's auc: 0.832251 [3336] Train's auc: 0.988086 Evaluation's auc: 0.832244 [3337] Train's auc: 0.98809 Evaluation's auc: 0.832229 [3338] Train's auc: 0.988096 Evaluation's auc: 0.832249 [3339] Train's auc: 0.988098 Evaluation's auc: 0.832228 [3340] Train's auc: 0.9881 Evaluation's auc: 0.832215 [3341] Train's auc: 0.988102 Evaluation's auc: 0.832209 [3342] Train's auc: 0.988107 Evaluation's auc: 0.832192 [3343] Train's auc: 0.988108 Evaluation's auc: 0.832179 [3344] Train's auc: 0.988109 Evaluation's auc: 0.832164 [3345] Train's auc: 0.988114 Evaluation's auc: 0.832176 [3346] Train's auc: 0.988115 Evaluation's auc: 0.832166 [3347] Train's auc: 0.988109 Evaluation's auc: 0.832171 [3348] Train's auc: 0.988112 Evaluation's auc: 0.832166 [3349] Train's auc: 0.988114 Evaluation's auc: 0.832182 [3350] Train's auc: 0.988113 Evaluation's auc: 0.832172 [3351] Train's auc: 0.988106 Evaluation's auc: 0.832208 [3352] Train's auc: 0.98811 Evaluation's auc: 0.832188 [3353] Train's auc: 0.988112 Evaluation's auc: 0.832186 [3354] Train's auc: 0.988113 Evaluation's auc: 0.832197 [3355] Train's auc: 0.988116 Evaluation's auc: 0.832191 [3356] Train's auc: 0.988127 Evaluation's auc: 0.832204 [3357] Train's auc: 0.988128 Evaluation's auc: 0.832195 [3358] Train's auc: 0.988129 Evaluation's auc: 0.832214 [3359] Train's auc: 0.988134 Evaluation's auc: 0.8322 [3360] Train's auc: 0.988144 Evaluation's auc: 0.832197 [3361] Train's auc: 0.988148 Evaluation's auc: 0.832187 [3362] Train's auc: 0.988154 Evaluation's auc: 0.832179 [3363] Train's auc: 0.988157 Evaluation's auc: 0.832176 [3364] Train's auc: 0.988162 Evaluation's auc: 0.832171 [3365] Train's auc: 0.988164 Evaluation's auc: 0.832169 [3366] Train's auc: 0.988167 Evaluation's auc: 0.832165 [3367] Train's auc: 0.988174 Evaluation's auc: 0.832175 [3368] Train's auc: 0.988171 Evaluation's auc: 0.832177 [3369] Train's auc: 0.98818 Evaluation's auc: 0.832197 [3370] Train's auc: 0.988187 Evaluation's auc: 0.832174 [3371] Train's auc: 0.988195 Evaluation's auc: 0.832157 [3372] Train's auc: 0.988201 Evaluation's auc: 0.832153 [3373] Train's auc: 0.988204 Evaluation's auc: 0.832145 [3374] Train's auc: 0.988205 Evaluation's auc: 0.832128 [3375] Train's auc: 0.988215 Evaluation's auc: 0.832112 [3376] Train's auc: 0.98822 Evaluation's auc: 0.832091 [3377] Train's auc: 0.988222 Evaluation's auc: 0.83209 [3378] Train's auc: 0.988228 Evaluation's auc: 0.832075 [3379] Train's auc: 0.988231 Evaluation's auc: 0.832054 [3380] Train's auc: 0.988244 Evaluation's auc: 0.832053 [3381] Train's auc: 0.988246 Evaluation's auc: 0.832072 [3382] Train's auc: 0.988248 Evaluation's auc: 0.832068 [3383] Train's auc: 0.988252 Evaluation's auc: 0.832049 [3384] Train's auc: 0.988252 Evaluation's auc: 0.832056 [3385] Train's auc: 0.988253 Evaluation's auc: 0.83205 [3386] Train's auc: 0.988255 Evaluation's auc: 0.83205 [3387] Train's auc: 0.988258 Evaluation's auc: 0.832025 [3388] Train's auc: 0.988261 Evaluation's auc: 0.832039 [3389] Train's auc: 0.988267 Evaluation's auc: 0.832026 [3390] Train's auc: 0.988267 Evaluation's auc: 0.83202 [3391] Train's auc: 0.98827 Evaluation's auc: 0.832013 [3392] Train's auc: 0.988267 Evaluation's auc: 0.832019 [3393] Train's auc: 0.988269 Evaluation's auc: 0.832036 [3394] Train's auc: 0.988279 Evaluation's auc: 0.832035 [3395] Train's auc: 0.988286 Evaluation's auc: 0.832011 [3396] Train's auc: 0.988288 Evaluation's auc: 0.832002 [3397] Train's auc: 0.988289 Evaluation's auc: 0.832003 [3398] Train's auc: 0.988293 Evaluation's auc: 0.831994 [3399] Train's auc: 0.988298 Evaluation's auc: 0.832008 [3400] Train's auc: 0.988301 Evaluation's auc: 0.832005 [3401] Train's auc: 0.988301 Evaluation's auc: 0.832005 [3402] Train's auc: 0.988298 Evaluation's auc: 0.832005 [3403] Train's auc: 0.988296 Evaluation's auc: 0.832009 [3404] Train's auc: 0.988296 Evaluation's auc: 0.832004 [3405] Train's auc: 0.988302 Evaluation's auc: 0.832018 [3406] Train's auc: 0.988306 Evaluation's auc: 0.831993 [3407] Train's auc: 0.988312 Evaluation's auc: 0.83199 [3408] Train's auc: 0.988318 Evaluation's auc: 0.831974 [3409] Train's auc: 0.988323 Evaluation's auc: 0.83195 [3410] Train's auc: 0.988327 Evaluation's auc: 0.831947 [3411] Train's auc: 0.988334 Evaluation's auc: 0.831946 [3412] Train's auc: 0.988342 Evaluation's auc: 0.831941 [3413] Train's auc: 0.988342 Evaluation's auc: 0.83194 [3414] Train's auc: 0.988345 Evaluation's auc: 0.831941 [3415] Train's auc: 0.988349 Evaluation's auc: 0.831947 [3416] Train's auc: 0.98836 Evaluation's auc: 0.831938 [3417] Train's auc: 0.988357 Evaluation's auc: 0.831918 [3418] Train's auc: 0.988355 Evaluation's auc: 0.831936 [3419] Train's auc: 0.98835 Evaluation's auc: 0.831936 [3420] Train's auc: 0.988358 Evaluation's auc: 0.831931 [3421] Train's auc: 0.988365 Evaluation's auc: 0.83191 [3422] Train's auc: 0.988369 Evaluation's auc: 0.831901 [3423] Train's auc: 0.988375 Evaluation's auc: 0.831901 [3424] Train's auc: 0.988371 Evaluation's auc: 0.831888 [3425] Train's auc: 0.988378 Evaluation's auc: 0.831882 [3426] Train's auc: 0.988379 Evaluation's auc: 0.831883 [3427] Train's auc: 0.988387 Evaluation's auc: 0.831899 [3428] Train's auc: 0.988397 Evaluation's auc: 0.831878 [3429] Train's auc: 0.988397 Evaluation's auc: 0.83187 [3430] Train's auc: 0.988397 Evaluation's auc: 0.831869 [3431] Train's auc: 0.9884 Evaluation's auc: 0.831877 [3432] Train's auc: 0.988406 Evaluation's auc: 0.831877 [3433] Train's auc: 0.98841 Evaluation's auc: 0.831868 [3434] Train's auc: 0.988412 Evaluation's auc: 0.831862 [3435] Train's auc: 0.988415 Evaluation's auc: 0.831867 [3436] Train's auc: 0.988415 Evaluation's auc: 0.831867 [3437] Train's auc: 0.988418 Evaluation's auc: 0.83185 [3438] Train's auc: 0.988426 Evaluation's auc: 0.831809 [3439] Train's auc: 0.988428 Evaluation's auc: 0.831821 [3440] Train's auc: 0.988428 Evaluation's auc: 0.831822 [3441] Train's auc: 0.988439 Evaluation's auc: 0.83181 [3442] Train's auc: 0.988439 Evaluation's auc: 0.831805 [3443] Train's auc: 0.988439 Evaluation's auc: 0.831813 [3444] Train's auc: 0.988443 Evaluation's auc: 0.831795 [3445] Train's auc: 0.988446 Evaluation's auc: 0.831774 [3446] Train's auc: 0.988449 Evaluation's auc: 0.831752 [3447] Train's auc: 0.98845 Evaluation's auc: 0.831738 [3448] Train's auc: 0.988453 Evaluation's auc: 0.831721 [3449] Train's auc: 0.988458 Evaluation's auc: 0.831715 [3450] Train's auc: 0.98846 Evaluation's auc: 0.831709 [3451] Train's auc: 0.988459 Evaluation's auc: 0.831721 [3452] Train's auc: 0.988464 Evaluation's auc: 0.831726 [3453] Train's auc: 0.988476 Evaluation's auc: 0.831737 [3454] Train's auc: 0.988483 Evaluation's auc: 0.831766 [3455] Train's auc: 0.988484 Evaluation's auc: 0.831753 [3456] Train's auc: 0.988489 Evaluation's auc: 0.831747 [3457] Train's auc: 0.98849 Evaluation's auc: 0.83173 [3458] Train's auc: 0.988491 Evaluation's auc: 0.831731 [3459] Train's auc: 0.988497 Evaluation's auc: 0.831717 [3460] Train's auc: 0.988498 Evaluation's auc: 0.831711 [3461] Train's auc: 0.988498 Evaluation's auc: 0.831714 [3462] Train's auc: 0.9885 Evaluation's auc: 0.831697 [3463] Train's auc: 0.988503 Evaluation's auc: 0.831704 [3464] Train's auc: 0.988507 Evaluation's auc: 0.831676 [3465] Train's auc: 0.988508 Evaluation's auc: 0.831688 [3466] Train's auc: 0.988507 Evaluation's auc: 0.831691 [3467] Train's auc: 0.988508 Evaluation's auc: 0.831691 [3468] Train's auc: 0.98851 Evaluation's auc: 0.831695 [3469] Train's auc: 0.988534 Evaluation's auc: 0.831672 [3470] Train's auc: 0.988539 Evaluation's auc: 0.831654 [3471] Train's auc: 0.988542 Evaluation's auc: 0.831642 [3472] Train's auc: 0.988541 Evaluation's auc: 0.83164 [3473] Train's auc: 0.988542 Evaluation's auc: 0.831674 [3474] Train's auc: 0.988543 Evaluation's auc: 0.831685 [3475] Train's auc: 0.98855 Evaluation's auc: 0.83167 [3476] Train's auc: 0.98855 Evaluation's auc: 0.831706 [3477] Train's auc: 0.988551 Evaluation's auc: 0.831708 [3478] Train's auc: 0.988552 Evaluation's auc: 0.831714 [3479] Train's auc: 0.988552 Evaluation's auc: 0.831715 [3480] Train's auc: 0.988554 Evaluation's auc: 0.831723 [3481] Train's auc: 0.988556 Evaluation's auc: 0.831731 [3482] Train's auc: 0.988561 Evaluation's auc: 0.831729 [3483] Train's auc: 0.988565 Evaluation's auc: 0.831715 [3484] Train's auc: 0.988567 Evaluation's auc: 0.831722 [3485] Train's auc: 0.988574 Evaluation's auc: 0.831704 [3486] Train's auc: 0.988573 Evaluation's auc: 0.831707 [3487] Train's auc: 0.988584 Evaluation's auc: 0.831709 [3488] Train's auc: 0.988586 Evaluation's auc: 0.831684 [3489] Train's auc: 0.988589 Evaluation's auc: 0.831684 [3490] Train's auc: 0.98859 Evaluation's auc: 0.831679 [3491] Train's auc: 0.98859 Evaluation's auc: 0.831687 [3492] Train's auc: 0.988593 Evaluation's auc: 0.831671 [3493] Train's auc: 0.988595 Evaluation's auc: 0.831667 [3494] Train's auc: 0.988598 Evaluation's auc: 0.831635 [3495] Train's auc: 0.988602 Evaluation's auc: 0.831612 [3496] Train's auc: 0.988607 Evaluation's auc: 0.831606 [3497] Train's auc: 0.988606 Evaluation's auc: 0.831628 [3498] Train's auc: 0.988615 Evaluation's auc: 0.831617 [3499] Train's auc: 0.988622 Evaluation's auc: 0.831656 [3500] Train's auc: 0.988634 Evaluation's auc: 0.831652 [3501] Train's auc: 0.988638 Evaluation's auc: 0.831646 [3502] Train's auc: 0.988645 Evaluation's auc: 0.831645 [3503] Train's auc: 0.988646 Evaluation's auc: 0.831638 [3504] Train's auc: 0.988651 Evaluation's auc: 0.83162 [3505] Train's auc: 0.988653 Evaluation's auc: 0.831612 [3506] Train's auc: 0.988657 Evaluation's auc: 0.831623 [3507] Train's auc: 0.988662 Evaluation's auc: 0.831633 [3508] Train's auc: 0.988664 Evaluation's auc: 0.83162 [3509] Train's auc: 0.988672 Evaluation's auc: 0.831644 [3510] Train's auc: 0.988675 Evaluation's auc: 0.831635 [3511] Train's auc: 0.988673 Evaluation's auc: 0.831628 [3512] Train's auc: 0.988677 Evaluation's auc: 0.831627 [3513] Train's auc: 0.988681 Evaluation's auc: 0.831646 [3514] Train's auc: 0.988693 Evaluation's auc: 0.831638 [3515] Train's auc: 0.988697 Evaluation's auc: 0.831649 [3516] Train's auc: 0.988699 Evaluation's auc: 0.831669 [3517] Train's auc: 0.9887 Evaluation's auc: 0.831662 [3518] Train's auc: 0.988701 Evaluation's auc: 0.831671 [3519] Train's auc: 0.98871 Evaluation's auc: 0.831656 [3520] Train's auc: 0.988711 Evaluation's auc: 0.831654 [3521] Train's auc: 0.988707 Evaluation's auc: 0.831665 [3522] Train's auc: 0.988707 Evaluation's auc: 0.831664 [3523] Train's auc: 0.988716 Evaluation's auc: 0.831656 [3524] Train's auc: 0.988718 Evaluation's auc: 0.831657 [3525] Train's auc: 0.988722 Evaluation's auc: 0.831682 [3526] Train's auc: 0.988725 Evaluation's auc: 0.831695 [3527] Train's auc: 0.988727 Evaluation's auc: 0.831697 [3528] Train's auc: 0.988739 Evaluation's auc: 0.831693 [3529] Train's auc: 0.988741 Evaluation's auc: 0.831679 [3530] Train's auc: 0.988741 Evaluation's auc: 0.831682 [3531] Train's auc: 0.988743 Evaluation's auc: 0.831678 [3532] Train's auc: 0.988752 Evaluation's auc: 0.831704 [3533] Train's auc: 0.988751 Evaluation's auc: 0.831695 [3534] Train's auc: 0.988751 Evaluation's auc: 0.831698 [3535] Train's auc: 0.988752 Evaluation's auc: 0.831693 [3536] Train's auc: 0.98876 Evaluation's auc: 0.831693 [3537] Train's auc: 0.988762 Evaluation's auc: 0.831689 [3538] Train's auc: 0.988765 Evaluation's auc: 0.831664 [3539] Train's auc: 0.988773 Evaluation's auc: 0.831653 [3540] Train's auc: 0.988771 Evaluation's auc: 0.831648 [3541] Train's auc: 0.988776 Evaluation's auc: 0.831627 [3542] Train's auc: 0.988777 Evaluation's auc: 0.831616 [3543] Train's auc: 0.988777 Evaluation's auc: 0.831614 [3544] Train's auc: 0.988778 Evaluation's auc: 0.831616 [3545] Train's auc: 0.988777 Evaluation's auc: 0.831613 [3546] Train's auc: 0.988779 Evaluation's auc: 0.8316 [3547] Train's auc: 0.988781 Evaluation's auc: 0.831589 [3548] Train's auc: 0.988789 Evaluation's auc: 0.831585 [3549] Train's auc: 0.988782 Evaluation's auc: 0.831595 [3550] Train's auc: 0.988788 Evaluation's auc: 0.831609 [3551] Train's auc: 0.988788 Evaluation's auc: 0.831609 [3552] Train's auc: 0.988787 Evaluation's auc: 0.83161 [3553] Train's auc: 0.988793 Evaluation's auc: 0.831603 [3554] Train's auc: 0.988793 Evaluation's auc: 0.831628 [3555] Train's auc: 0.988793 Evaluation's auc: 0.83162 [3556] Train's auc: 0.988795 Evaluation's auc: 0.831606 [3557] Train's auc: 0.988798 Evaluation's auc: 0.831596 [3558] Train's auc: 0.988807 Evaluation's auc: 0.831584 [3559] Train's auc: 0.988811 Evaluation's auc: 0.831584 [3560] Train's auc: 0.988811 Evaluation's auc: 0.831588 [3561] Train's auc: 0.988814 Evaluation's auc: 0.831551 [3562] Train's auc: 0.988819 Evaluation's auc: 0.831549 [3563] Train's auc: 0.988823 Evaluation's auc: 0.83155 [3564] Train's auc: 0.988826 Evaluation's auc: 0.831538 [3565] Train's auc: 0.988828 Evaluation's auc: 0.83153 [3566] Train's auc: 0.988834 Evaluation's auc: 0.831513 [3567] Train's auc: 0.988831 Evaluation's auc: 0.831558 [3568] Train's auc: 0.988834 Evaluation's auc: 0.831551 [3569] Train's auc: 0.988835 Evaluation's auc: 0.831545 [3570] Train's auc: 0.98884 Evaluation's auc: 0.83156 [3571] Train's auc: 0.988841 Evaluation's auc: 0.831546 [3572] Train's auc: 0.988841 Evaluation's auc: 0.831543 [3573] Train's auc: 0.98885 Evaluation's auc: 0.831533 [3574] Train's auc: 0.988855 Evaluation's auc: 0.831495 [3575] Train's auc: 0.988855 Evaluation's auc: 0.831499 [3576] Train's auc: 0.988851 Evaluation's auc: 0.831496 [3577] Train's auc: 0.988851 Evaluation's auc: 0.8315 [3578] Train's auc: 0.988852 Evaluation's auc: 0.831526 [3579] Train's auc: 0.988854 Evaluation's auc: 0.831531 [3580] Train's auc: 0.988854 Evaluation's auc: 0.83155 [3581] Train's auc: 0.988855 Evaluation's auc: 0.831551 [3582] Train's auc: 0.988857 Evaluation's auc: 0.831562 [3583] Train's auc: 0.988866 Evaluation's auc: 0.831564 [3584] Train's auc: 0.988872 Evaluation's auc: 0.83156 [3585] Train's auc: 0.988874 Evaluation's auc: 0.831587 [3586] Train's auc: 0.988893 Evaluation's auc: 0.831589 [3587] Train's auc: 0.988896 Evaluation's auc: 0.831577 [3588] Train's auc: 0.988901 Evaluation's auc: 0.831606 [3589] Train's auc: 0.988905 Evaluation's auc: 0.831585 [3590] Train's auc: 0.988908 Evaluation's auc: 0.831578 [3591] Train's auc: 0.988907 Evaluation's auc: 0.831589 [3592] Train's auc: 0.98891 Evaluation's auc: 0.831601 [3593] Train's auc: 0.98891 Evaluation's auc: 0.831601 [3594] Train's auc: 0.988914 Evaluation's auc: 0.831603 [3595] Train's auc: 0.988914 Evaluation's auc: 0.831605 [3596] Train's auc: 0.988914 Evaluation's auc: 0.831609 [3597] Train's auc: 0.988913 Evaluation's auc: 0.831605 [3598] Train's auc: 0.988917 Evaluation's auc: 0.831613 [3599] Train's auc: 0.988918 Evaluation's auc: 0.831609 [3600] Train's auc: 0.988922 Evaluation's auc: 0.831598 [3601] Train's auc: 0.988924 Evaluation's auc: 0.831597 [3602] Train's auc: 0.988928 Evaluation's auc: 0.831596 [3603] Train's auc: 0.988929 Evaluation's auc: 0.831587 [3604] Train's auc: 0.988931 Evaluation's auc: 0.831554 [3605] Train's auc: 0.988937 Evaluation's auc: 0.831554 [3606] Train's auc: 0.98894 Evaluation's auc: 0.83155 [3607] Train's auc: 0.988946 Evaluation's auc: 0.831538 [3608] Train's auc: 0.988948 Evaluation's auc: 0.831541 [3609] Train's auc: 0.988949 Evaluation's auc: 0.831529 [3610] Train's auc: 0.988954 Evaluation's auc: 0.831543 [3611] Train's auc: 0.988954 Evaluation's auc: 0.831543 [3612] Train's auc: 0.988954 Evaluation's auc: 0.831534 [3613] Train's auc: 0.988955 Evaluation's auc: 0.83153 [3614] Train's auc: 0.98896 Evaluation's auc: 0.831528 [3615] Train's auc: 0.988962 Evaluation's auc: 0.831524 [3616] Train's auc: 0.988961 Evaluation's auc: 0.831534 [3617] Train's auc: 0.988965 Evaluation's auc: 0.83153 [3618] Train's auc: 0.988966 Evaluation's auc: 0.831524 [3619] Train's auc: 0.988968 Evaluation's auc: 0.831522 [3620] Train's auc: 0.988969 Evaluation's auc: 0.831523 [3621] Train's auc: 0.988972 Evaluation's auc: 0.831519 [3622] Train's auc: 0.988984 Evaluation's auc: 0.83152 [3623] Train's auc: 0.988983 Evaluation's auc: 0.831519 [3624] Train's auc: 0.988987 Evaluation's auc: 0.831523 [3625] Train's auc: 0.988985 Evaluation's auc: 0.831526 [3626] Train's auc: 0.988988 Evaluation's auc: 0.831522 [3627] Train's auc: 0.988991 Evaluation's auc: 0.831516 [3628] Train's auc: 0.988996 Evaluation's auc: 0.83152 [3629] Train's auc: 0.988997 Evaluation's auc: 0.83151 [3630] Train's auc: 0.989002 Evaluation's auc: 0.831529 [3631] Train's auc: 0.989003 Evaluation's auc: 0.831528 [3632] Train's auc: 0.989007 Evaluation's auc: 0.831514 [3633] Train's auc: 0.989008 Evaluation's auc: 0.831515 [3634] Train's auc: 0.989005 Evaluation's auc: 0.831514 [3635] Train's auc: 0.989006 Evaluation's auc: 0.831506 [3636] Train's auc: 0.989007 Evaluation's auc: 0.831509 [3637] Train's auc: 0.989008 Evaluation's auc: 0.831527 [3638] Train's auc: 0.989014 Evaluation's auc: 0.831513 [3639] Train's auc: 0.989015 Evaluation's auc: 0.831488 [3640] Train's auc: 0.989017 Evaluation's auc: 0.831481 [3641] Train's auc: 0.989022 Evaluation's auc: 0.831477 [3642] Train's auc: 0.989022 Evaluation's auc: 0.831477 [3643] Train's auc: 0.989025 Evaluation's auc: 0.831479 [3644] Train's auc: 0.989035 Evaluation's auc: 0.831485 [3645] Train's auc: 0.989035 Evaluation's auc: 0.831481 [3646] Train's auc: 0.989034 Evaluation's auc: 0.831492 [3647] Train's auc: 0.989036 Evaluation's auc: 0.831496 [3648] Train's auc: 0.989039 Evaluation's auc: 0.831487 [3649] Train's auc: 0.989041 Evaluation's auc: 0.83146 [3650] Train's auc: 0.98904 Evaluation's auc: 0.831477 [3651] Train's auc: 0.98904 Evaluation's auc: 0.83148 [3652] Train's auc: 0.989043 Evaluation's auc: 0.831469 [3653] Train's auc: 0.989046 Evaluation's auc: 0.831468 [3654] Train's auc: 0.989046 Evaluation's auc: 0.83147 [3655] Train's auc: 0.989047 Evaluation's auc: 0.831471 [3656] Train's auc: 0.989048 Evaluation's auc: 0.831477 [3657] Train's auc: 0.989049 Evaluation's auc: 0.831461 [3658] Train's auc: 0.98905 Evaluation's auc: 0.831461 [3659] Train's auc: 0.989049 Evaluation's auc: 0.83145 [3660] Train's auc: 0.989052 Evaluation's auc: 0.831468 [3661] Train's auc: 0.989057 Evaluation's auc: 0.831454 [3662] Train's auc: 0.989057 Evaluation's auc: 0.831453 [3663] Train's auc: 0.989059 Evaluation's auc: 0.83144 [3664] Train's auc: 0.98906 Evaluation's auc: 0.831421 [3665] Train's auc: 0.989063 Evaluation's auc: 0.831425 [3666] Train's auc: 0.989075 Evaluation's auc: 0.831424 [3667] Train's auc: 0.989075 Evaluation's auc: 0.831423 [3668] Train's auc: 0.989078 Evaluation's auc: 0.83144 [3669] Train's auc: 0.989084 Evaluation's auc: 0.831443 [3670] Train's auc: 0.989091 Evaluation's auc: 0.831444 [3671] Train's auc: 0.989094 Evaluation's auc: 0.831431 [3672] Train's auc: 0.989097 Evaluation's auc: 0.831419 [3673] Train's auc: 0.989097 Evaluation's auc: 0.831418 [3674] Train's auc: 0.989099 Evaluation's auc: 0.831401 [3675] Train's auc: 0.989105 Evaluation's auc: 0.831392 [3676] Train's auc: 0.989106 Evaluation's auc: 0.831391 [3677] Train's auc: 0.989109 Evaluation's auc: 0.831382 [3678] Train's auc: 0.989111 Evaluation's auc: 0.831347 [3679] Train's auc: 0.989112 Evaluation's auc: 0.831348 [3680] Train's auc: 0.989113 Evaluation's auc: 0.831354 [3681] Train's auc: 0.989114 Evaluation's auc: 0.831357 [3682] Train's auc: 0.989116 Evaluation's auc: 0.831346 [3683] Train's auc: 0.989116 Evaluation's auc: 0.831343 [3684] Train's auc: 0.989121 Evaluation's auc: 0.831331 [3685] Train's auc: 0.989124 Evaluation's auc: 0.831339 [3686] Train's auc: 0.989128 Evaluation's auc: 0.831332 [3687] Train's auc: 0.989135 Evaluation's auc: 0.831336 [3688] Train's auc: 0.989143 Evaluation's auc: 0.831317 [3689] Train's auc: 0.989144 Evaluation's auc: 0.831315 [3690] Train's auc: 0.989147 Evaluation's auc: 0.831325 [3691] Train's auc: 0.989148 Evaluation's auc: 0.83131 [3692] Train's auc: 0.989148 Evaluation's auc: 0.831299 [3693] Train's auc: 0.989148 Evaluation's auc: 0.831312 [3694] Train's auc: 0.989148 Evaluation's auc: 0.831307 [3695] Train's auc: 0.989154 Evaluation's auc: 0.831322 [3696] Train's auc: 0.989158 Evaluation's auc: 0.831329 [3697] Train's auc: 0.989154 Evaluation's auc: 0.831334 [3698] Train's auc: 0.989156 Evaluation's auc: 0.831313 [3699] Train's auc: 0.98916 Evaluation's auc: 0.831319 [3700] Train's auc: 0.989162 Evaluation's auc: 0.831319 [3701] Train's auc: 0.989163 Evaluation's auc: 0.831315 [3702] Train's auc: 0.989163 Evaluation's auc: 0.831323 [3703] Train's auc: 0.989164 Evaluation's auc: 0.831321 [3704] Train's auc: 0.989166 Evaluation's auc: 0.831301 [3705] Train's auc: 0.989169 Evaluation's auc: 0.831276 [3706] Train's auc: 0.98917 Evaluation's auc: 0.831274 [3707] Train's auc: 0.989171 Evaluation's auc: 0.831273 [3708] Train's auc: 0.989173 Evaluation's auc: 0.831265 [3709] Train's auc: 0.989173 Evaluation's auc: 0.831262 [3710] Train's auc: 0.989174 Evaluation's auc: 0.831263 [3711] Train's auc: 0.989174 Evaluation's auc: 0.831263 [3712] Train's auc: 0.989173 Evaluation's auc: 0.831263 [3713] Train's auc: 0.989175 Evaluation's auc: 0.831272 [3714] Train's auc: 0.989182 Evaluation's auc: 0.831255 [3715] Train's auc: 0.989182 Evaluation's auc: 0.831253 [3716] Train's auc: 0.989182 Evaluation's auc: 0.831253 [3717] Train's auc: 0.989183 Evaluation's auc: 0.831242 [3718] Train's auc: 0.989185 Evaluation's auc: 0.831226 [3719] Train's auc: 0.989187 Evaluation's auc: 0.831216 [3720] Train's auc: 0.989188 Evaluation's auc: 0.831222 [3721] Train's auc: 0.98919 Evaluation's auc: 0.831212 [3722] Train's auc: 0.98919 Evaluation's auc: 0.831212 [3723] Train's auc: 0.989191 Evaluation's auc: 0.831221 [3724] Train's auc: 0.989194 Evaluation's auc: 0.831221 [3725] Train's auc: 0.989197 Evaluation's auc: 0.83122 [3726] Train's auc: 0.989199 Evaluation's auc: 0.831215 [3727] Train's auc: 0.989207 Evaluation's auc: 0.831224 [3728] Train's auc: 0.98921 Evaluation's auc: 0.831221 [3729] Train's auc: 0.98921 Evaluation's auc: 0.831217 [3730] Train's auc: 0.989217 Evaluation's auc: 0.831234 [3731] Train's auc: 0.989217 Evaluation's auc: 0.83123 [3732] Train's auc: 0.989217 Evaluation's auc: 0.831236 [3733] Train's auc: 0.989217 Evaluation's auc: 0.831236 [3734] Train's auc: 0.989217 Evaluation's auc: 0.831236 [3735] Train's auc: 0.989217 Evaluation's auc: 0.831233 [3736] Train's auc: 0.989217 Evaluation's auc: 0.831246 [3737] Train's auc: 0.989219 Evaluation's auc: 0.831225 [3738] Train's auc: 0.989221 Evaluation's auc: 0.831224 [3739] Train's auc: 0.98922 Evaluation's auc: 0.831216 [3740] Train's auc: 0.989225 Evaluation's auc: 0.831196 [3741] Train's auc: 0.989221 Evaluation's auc: 0.831189 [3742] Train's auc: 0.98923 Evaluation's auc: 0.831167 [3743] Train's auc: 0.98923 Evaluation's auc: 0.831163 [3744] Train's auc: 0.989232 Evaluation's auc: 0.831163 [3745] Train's auc: 0.989232 Evaluation's auc: 0.831163 [3746] Train's auc: 0.989235 Evaluation's auc: 0.831186 [3747] Train's auc: 0.989237 Evaluation's auc: 0.831182 [3748] Train's auc: 0.989238 Evaluation's auc: 0.831183 [3749] Train's auc: 0.989244 Evaluation's auc: 0.831175 [3750] Train's auc: 0.989247 Evaluation's auc: 0.831185 [3751] Train's auc: 0.989247 Evaluation's auc: 0.831183 [3752] Train's auc: 0.989251 Evaluation's auc: 0.831184 [3753] Train's auc: 0.989249 Evaluation's auc: 0.831184 [3754] Train's auc: 0.989252 Evaluation's auc: 0.831164 [3755] Train's auc: 0.989252 Evaluation's auc: 0.83117 [3756] Train's auc: 0.98925 Evaluation's auc: 0.831189 [3757] Train's auc: 0.989254 Evaluation's auc: 0.831194 [3758] Train's auc: 0.989255 Evaluation's auc: 0.831218 [3759] Train's auc: 0.989254 Evaluation's auc: 0.831226 [3760] Train's auc: 0.989268 Evaluation's auc: 0.831215 [3761] Train's auc: 0.989268 Evaluation's auc: 0.831208 [3762] Train's auc: 0.989268 Evaluation's auc: 0.831212 [3763] Train's auc: 0.989268 Evaluation's auc: 0.831211 [3764] Train's auc: 0.989271 Evaluation's auc: 0.831209 [3765] Train's auc: 0.989271 Evaluation's auc: 0.831213 [3766] Train's auc: 0.98927 Evaluation's auc: 0.831215 [3767] Train's auc: 0.98927 Evaluation's auc: 0.831216 [3768] Train's auc: 0.98927 Evaluation's auc: 0.831212 [3769] Train's auc: 0.989271 Evaluation's auc: 0.831224 [3770] Train's auc: 0.989269 Evaluation's auc: 0.831223 [3771] Train's auc: 0.989268 Evaluation's auc: 0.831227 [3772] Train's auc: 0.989271 Evaluation's auc: 0.831221 [3773] Train's auc: 0.989277 Evaluation's auc: 0.831216 [3774] Train's auc: 0.98928 Evaluation's auc: 0.831229 [3775] Train's auc: 0.989282 Evaluation's auc: 0.831244 [3776] Train's auc: 0.989282 Evaluation's auc: 0.831226 [3777] Train's auc: 0.989283 Evaluation's auc: 0.831219 [3778] Train's auc: 0.989288 Evaluation's auc: 0.831218 [3779] Train's auc: 0.989293 Evaluation's auc: 0.831221 [3780] Train's auc: 0.989293 Evaluation's auc: 0.831211 [3781] Train's auc: 0.989293 Evaluation's auc: 0.831212 [3782] Train's auc: 0.989295 Evaluation's auc: 0.831198 [3783] Train's auc: 0.989296 Evaluation's auc: 0.831191 [3784] Train's auc: 0.989298 Evaluation's auc: 0.831189 [3785] Train's auc: 0.989295 Evaluation's auc: 0.831225 [3786] Train's auc: 0.989295 Evaluation's auc: 0.831224 [3787] Train's auc: 0.9893 Evaluation's auc: 0.831235 [3788] Train's auc: 0.989302 Evaluation's auc: 0.831226 [3789] Train's auc: 0.989303 Evaluation's auc: 0.83123 [3790] Train's auc: 0.989303 Evaluation's auc: 0.83123 [3791] Train's auc: 0.989305 Evaluation's auc: 0.831232 [3792] Train's auc: 0.989308 Evaluation's auc: 0.831215 [3793] Train's auc: 0.98931 Evaluation's auc: 0.831224 [3794] Train's auc: 0.989311 Evaluation's auc: 0.831223 [3795] Train's auc: 0.989311 Evaluation's auc: 0.831224 [3796] Train's auc: 0.98931 Evaluation's auc: 0.831217 [3797] Train's auc: 0.989315 Evaluation's auc: 0.831213 [3798] Train's auc: 0.989315 Evaluation's auc: 0.831211 [3799] Train's auc: 0.989316 Evaluation's auc: 0.831205 [3800] Train's auc: 0.98932 Evaluation's auc: 0.831197 [3801] Train's auc: 0.989323 Evaluation's auc: 0.831205 [3802] Train's auc: 0.989325 Evaluation's auc: 0.831204 [3803] Train's auc: 0.989326 Evaluation's auc: 0.831199 [3804] Train's auc: 0.989328 Evaluation's auc: 0.831193 [3805] Train's auc: 0.989331 Evaluation's auc: 0.831191 [3806] Train's auc: 0.989336 Evaluation's auc: 0.831174 [3807] Train's auc: 0.989338 Evaluation's auc: 0.831176 [3808] Train's auc: 0.989337 Evaluation's auc: 0.83118 [3809] Train's auc: 0.989338 Evaluation's auc: 0.831177 [3810] Train's auc: 0.98934 Evaluation's auc: 0.831158 [3811] Train's auc: 0.989344 Evaluation's auc: 0.831155 [3812] Train's auc: 0.989346 Evaluation's auc: 0.831154 [3813] Train's auc: 0.989352 Evaluation's auc: 0.831157 [3814] Train's auc: 0.989357 Evaluation's auc: 0.831166 [3815] Train's auc: 0.989362 Evaluation's auc: 0.831145 [3816] Train's auc: 0.98937 Evaluation's auc: 0.831149 [3817] Train's auc: 0.989372 Evaluation's auc: 0.831153 [3818] Train's auc: 0.989376 Evaluation's auc: 0.83116 [3819] Train's auc: 0.989378 Evaluation's auc: 0.831157 [3820] Train's auc: 0.98938 Evaluation's auc: 0.831144 [3821] Train's auc: 0.989391 Evaluation's auc: 0.831116 [3822] Train's auc: 0.989391 Evaluation's auc: 0.831131 [3823] Train's auc: 0.98939 Evaluation's auc: 0.831132 [3824] Train's auc: 0.989391 Evaluation's auc: 0.831136 [3825] Train's auc: 0.989391 Evaluation's auc: 0.831136 [3826] Train's auc: 0.989391 Evaluation's auc: 0.831136 [3827] Train's auc: 0.989395 Evaluation's auc: 0.831129 [3828] Train's auc: 0.989395 Evaluation's auc: 0.831132 [3829] Train's auc: 0.989399 Evaluation's auc: 0.831116 [3830] Train's auc: 0.989396 Evaluation's auc: 0.831133 [3831] Train's auc: 0.989401 Evaluation's auc: 0.831127 [3832] Train's auc: 0.989403 Evaluation's auc: 0.831117 [3833] Train's auc: 0.989403 Evaluation's auc: 0.831095 [3834] Train's auc: 0.989404 Evaluation's auc: 0.8311 [3835] Train's auc: 0.989403 Evaluation's auc: 0.831104 [3836] Train's auc: 0.989404 Evaluation's auc: 0.831101 [3837] Train's auc: 0.989407 Evaluation's auc: 0.831104 [3838] Train's auc: 0.989413 Evaluation's auc: 0.831101 [3839] Train's auc: 0.989413 Evaluation's auc: 0.831104 [3840] Train's auc: 0.989417 Evaluation's auc: 0.831125 [3841] Train's auc: 0.989427 Evaluation's auc: 0.831128 [3842] Train's auc: 0.98943 Evaluation's auc: 0.831123 [3843] Train's auc: 0.989437 Evaluation's auc: 0.83111 [3844] Train's auc: 0.989443 Evaluation's auc: 0.831099 [3845] Train's auc: 0.989439 Evaluation's auc: 0.831108 [3846] Train's auc: 0.989439 Evaluation's auc: 0.831106 [3847] Train's auc: 0.98944 Evaluation's auc: 0.83111 [3848] Train's auc: 0.989437 Evaluation's auc: 0.831127 [3849] Train's auc: 0.989437 Evaluation's auc: 0.831126 [3850] Train's auc: 0.989438 Evaluation's auc: 0.831125 [3851] Train's auc: 0.98944 Evaluation's auc: 0.831137 [3852] Train's auc: 0.989441 Evaluation's auc: 0.831135 [3853] Train's auc: 0.989442 Evaluation's auc: 0.831132 [3854] Train's auc: 0.989445 Evaluation's auc: 0.831127 [3855] Train's auc: 0.989443 Evaluation's auc: 0.831132 [3856] Train's auc: 0.989445 Evaluation's auc: 0.831142 [3857] Train's auc: 0.989445 Evaluation's auc: 0.831142 [3858] Train's auc: 0.989447 Evaluation's auc: 0.831146 [3859] Train's auc: 0.989451 Evaluation's auc: 0.831138 [3860] Train's auc: 0.98945 Evaluation's auc: 0.831144 [3861] Train's auc: 0.989453 Evaluation's auc: 0.831136 [3862] Train's auc: 0.989455 Evaluation's auc: 0.831122 [3863] Train's auc: 0.989457 Evaluation's auc: 0.831118 [3864] Train's auc: 0.989457 Evaluation's auc: 0.831121 [3865] Train's auc: 0.98946 Evaluation's auc: 0.831122 [3866] Train's auc: 0.989461 Evaluation's auc: 0.831116 [3867] Train's auc: 0.989466 Evaluation's auc: 0.831127 [3868] Train's auc: 0.989472 Evaluation's auc: 0.831107 [3869] Train's auc: 0.989471 Evaluation's auc: 0.8311 [3870] Train's auc: 0.989471 Evaluation's auc: 0.831087 [3871] Train's auc: 0.989476 Evaluation's auc: 0.831091 [3872] Train's auc: 0.989481 Evaluation's auc: 0.831089 [3873] Train's auc: 0.989488 Evaluation's auc: 0.83109 [3874] Train's auc: 0.989488 Evaluation's auc: 0.831088 [3875] Train's auc: 0.989489 Evaluation's auc: 0.831083 [3876] Train's auc: 0.98949 Evaluation's auc: 0.831089 [3877] Train's auc: 0.989491 Evaluation's auc: 0.831074 [3878] Train's auc: 0.989487 Evaluation's auc: 0.831075 [3879] Train's auc: 0.989492 Evaluation's auc: 0.831057 [3880] Train's auc: 0.989493 Evaluation's auc: 0.831049 [3881] Train's auc: 0.989498 Evaluation's auc: 0.831034 [3882] Train's auc: 0.989501 Evaluation's auc: 0.83104 [3883] Train's auc: 0.989504 Evaluation's auc: 0.83104 [3884] Train's auc: 0.989506 Evaluation's auc: 0.831023 [3885] Train's auc: 0.989506 Evaluation's auc: 0.831022 [3886] Train's auc: 0.989506 Evaluation's auc: 0.831022 [3887] Train's auc: 0.989507 Evaluation's auc: 0.831041 [3888] Train's auc: 0.98952 Evaluation's auc: 0.831039 [3889] Train's auc: 0.98952 Evaluation's auc: 0.831037 [3890] Train's auc: 0.989521 Evaluation's auc: 0.831041 [3891] Train's auc: 0.989526 Evaluation's auc: 0.83104 [3892] Train's auc: 0.989526 Evaluation's auc: 0.83104 [3893] Train's auc: 0.989523 Evaluation's auc: 0.831018 [3894] Train's auc: 0.989525 Evaluation's auc: 0.830999 [3895] Train's auc: 0.989528 Evaluation's auc: 0.830997 [3896] Train's auc: 0.989526 Evaluation's auc: 0.831003 [3897] Train's auc: 0.989522 Evaluation's auc: 0.831016 [3898] Train's auc: 0.989525 Evaluation's auc: 0.83101 [3899] Train's auc: 0.989531 Evaluation's auc: 0.831014 [3900] Train's auc: 0.989534 Evaluation's auc: 0.831002 [3901] Train's auc: 0.989536 Evaluation's auc: 0.830979 [3902] Train's auc: 0.989538 Evaluation's auc: 0.830977 [3903] Train's auc: 0.989541 Evaluation's auc: 0.831023 [3904] Train's auc: 0.989543 Evaluation's auc: 0.83103 [3905] Train's auc: 0.989543 Evaluation's auc: 0.83103 [3906] Train's auc: 0.989543 Evaluation's auc: 0.83103 [3907] Train's auc: 0.989543 Evaluation's auc: 0.831031 [3908] Train's auc: 0.989545 Evaluation's auc: 0.83102 [3909] Train's auc: 0.98955 Evaluation's auc: 0.831032 [3910] Train's auc: 0.98955 Evaluation's auc: 0.831033 [3911] Train's auc: 0.989555 Evaluation's auc: 0.831035 [3912] Train's auc: 0.989558 Evaluation's auc: 0.831036 [3913] Train's auc: 0.989558 Evaluation's auc: 0.831036 [3914] Train's auc: 0.989559 Evaluation's auc: 0.831032 [3915] Train's auc: 0.989557 Evaluation's auc: 0.831019 [3916] Train's auc: 0.989557 Evaluation's auc: 0.831018 [3917] Train's auc: 0.989557 Evaluation's auc: 0.831018 [3918] Train's auc: 0.989557 Evaluation's auc: 0.831012 [3919] Train's auc: 0.989557 Evaluation's auc: 0.831014 [3920] Train's auc: 0.989559 Evaluation's auc: 0.83103 [3921] Train's auc: 0.989561 Evaluation's auc: 0.831004 [3922] Train's auc: 0.989562 Evaluation's auc: 0.830998 [3923] Train's auc: 0.989563 Evaluation's auc: 0.830991 [3924] Train's auc: 0.989567 Evaluation's auc: 0.830976 [3925] Train's auc: 0.989569 Evaluation's auc: 0.830977 [3926] Train's auc: 0.989571 Evaluation's auc: 0.830964 [3927] Train's auc: 0.989577 Evaluation's auc: 0.830941 [3928] Train's auc: 0.989577 Evaluation's auc: 0.830941 [3929] Train's auc: 0.989574 Evaluation's auc: 0.830934 [3930] Train's auc: 0.989573 Evaluation's auc: 0.830938 [3931] Train's auc: 0.989576 Evaluation's auc: 0.830929 [3932] Train's auc: 0.989577 Evaluation's auc: 0.830927 [3933] Train's auc: 0.98958 Evaluation's auc: 0.83092 [3934] Train's auc: 0.989582 Evaluation's auc: 0.830915 [3935] Train's auc: 0.989584 Evaluation's auc: 0.830905 [3936] Train's auc: 0.989585 Evaluation's auc: 0.830903 [3937] Train's auc: 0.989585 Evaluation's auc: 0.830901 [3938] Train's auc: 0.98959 Evaluation's auc: 0.830912 [3939] Train's auc: 0.989589 Evaluation's auc: 0.830942 [3940] Train's auc: 0.989593 Evaluation's auc: 0.830925 [3941] Train's auc: 0.9896 Evaluation's auc: 0.830926 [3942] Train's auc: 0.989609 Evaluation's auc: 0.830943 [3943] Train's auc: 0.989607 Evaluation's auc: 0.830951 [3944] Train's auc: 0.989611 Evaluation's auc: 0.830952 [3945] Train's auc: 0.989613 Evaluation's auc: 0.830948 [3946] Train's auc: 0.98962 Evaluation's auc: 0.830948 [3947] Train's auc: 0.989622 Evaluation's auc: 0.83094 [3948] Train's auc: 0.989628 Evaluation's auc: 0.83097 [3949] Train's auc: 0.98963 Evaluation's auc: 0.830958 [3950] Train's auc: 0.989633 Evaluation's auc: 0.830951 [3951] Train's auc: 0.989633 Evaluation's auc: 0.830951 [3952] Train's auc: 0.989636 Evaluation's auc: 0.830963 [3953] Train's auc: 0.989636 Evaluation's auc: 0.830963 [3954] Train's auc: 0.989635 Evaluation's auc: 0.830964 [3955] Train's auc: 0.989636 Evaluation's auc: 0.830966 [3956] Train's auc: 0.989639 Evaluation's auc: 0.830959 [3957] Train's auc: 0.98964 Evaluation's auc: 0.83097 [3958] Train's auc: 0.989642 Evaluation's auc: 0.830966 [3959] Train's auc: 0.989643 Evaluation's auc: 0.830965 [3960] Train's auc: 0.989644 Evaluation's auc: 0.830969 [3961] Train's auc: 0.989644 Evaluation's auc: 0.83098 [3962] Train's auc: 0.989641 Evaluation's auc: 0.83097 [3963] Train's auc: 0.989644 Evaluation's auc: 0.830962 [3964] Train's auc: 0.989646 Evaluation's auc: 0.830952 [3965] Train's auc: 0.989653 Evaluation's auc: 0.830952 [3966] Train's auc: 0.989653 Evaluation's auc: 0.830954 [3967] Train's auc: 0.989654 Evaluation's auc: 0.830942 [3968] Train's auc: 0.989654 Evaluation's auc: 0.830942 [3969] Train's auc: 0.989654 Evaluation's auc: 0.83097 [3970] Train's auc: 0.989655 Evaluation's auc: 0.83098 [3971] Train's auc: 0.989658 Evaluation's auc: 0.83097 [3972] Train's auc: 0.989659 Evaluation's auc: 0.830966 [3973] Train's auc: 0.989663 Evaluation's auc: 0.830963 [3974] Train's auc: 0.989663 Evaluation's auc: 0.830967 [3975] Train's auc: 0.989667 Evaluation's auc: 0.830961 [3976] Train's auc: 0.989674 Evaluation's auc: 0.830963 [3977] Train's auc: 0.989671 Evaluation's auc: 0.830959 [3978] Train's auc: 0.989673 Evaluation's auc: 0.830953 [3979] Train's auc: 0.989668 Evaluation's auc: 0.830964 [3980] Train's auc: 0.989669 Evaluation's auc: 0.830966 [3981] Train's auc: 0.989672 Evaluation's auc: 0.830952 [3982] Train's auc: 0.989674 Evaluation's auc: 0.830935 [3983] Train's auc: 0.989675 Evaluation's auc: 0.830926 [3984] Train's auc: 0.989678 Evaluation's auc: 0.830934 [3985] Train's auc: 0.989678 Evaluation's auc: 0.830946 [3986] Train's auc: 0.989678 Evaluation's auc: 0.830951 [3987] Train's auc: 0.989679 Evaluation's auc: 0.830958 [3988] Train's auc: 0.989685 Evaluation's auc: 0.830947 [3989] Train's auc: 0.989688 Evaluation's auc: 0.830938 [3990] Train's auc: 0.989689 Evaluation's auc: 0.830945 [3991] Train's auc: 0.989693 Evaluation's auc: 0.830965 [3992] Train's auc: 0.989698 Evaluation's auc: 0.830964 [3993] Train's auc: 0.989698 Evaluation's auc: 0.830964 [3994] Train's auc: 0.989699 Evaluation's auc: 0.830954 [3995] Train's auc: 0.989699 Evaluation's auc: 0.830953 [3996] Train's auc: 0.9897 Evaluation's auc: 0.830952 [3997] Train's auc: 0.9897 Evaluation's auc: 0.830953 [3998] Train's auc: 0.9897 Evaluation's auc: 0.830953 [3999] Train's auc: 0.989704 Evaluation's auc: 0.830945 [4000] Train's auc: 0.989709 Evaluation's auc: 0.830965 [4001] Train's auc: 0.989709 Evaluation's auc: 0.830959 [4002] Train's auc: 0.989709 Evaluation's auc: 0.830957 [4003] Train's auc: 0.989711 Evaluation's auc: 0.830962 [4004] Train's auc: 0.989711 Evaluation's auc: 0.830964 [4005] Train's auc: 0.989711 Evaluation's auc: 0.830964 [4006] Train's auc: 0.989713 Evaluation's auc: 0.830965 [4007] Train's auc: 0.989716 Evaluation's auc: 0.830958 [4008] Train's auc: 0.989719 Evaluation's auc: 0.830963 [4009] Train's auc: 0.989728 Evaluation's auc: 0.830987 [4010] Train's auc: 0.98973 Evaluation's auc: 0.830974 [4011] Train's auc: 0.989733 Evaluation's auc: 0.830976 [4012] Train's auc: 0.989734 Evaluation's auc: 0.830979 [4013] Train's auc: 0.989734 Evaluation's auc: 0.830979 [4014] Train's auc: 0.989735 Evaluation's auc: 0.830973 [4015] Train's auc: 0.98974 Evaluation's auc: 0.830973 [4016] Train's auc: 0.989741 Evaluation's auc: 0.830974 [4017] Train's auc: 0.98974 Evaluation's auc: 0.830971 [4018] Train's auc: 0.989742 Evaluation's auc: 0.830954 [4019] Train's auc: 0.989744 Evaluation's auc: 0.830947 [4020] Train's auc: 0.989744 Evaluation's auc: 0.830946 [4021] Train's auc: 0.98974 Evaluation's auc: 0.830951 [4022] Train's auc: 0.989741 Evaluation's auc: 0.830958 [4023] Train's auc: 0.989742 Evaluation's auc: 0.830959 [4024] Train's auc: 0.989742 Evaluation's auc: 0.830957 [4025] Train's auc: 0.989748 Evaluation's auc: 0.83094 [4026] Train's auc: 0.989748 Evaluation's auc: 0.83094 [4027] Train's auc: 0.989752 Evaluation's auc: 0.830915 [4028] Train's auc: 0.989757 Evaluation's auc: 0.830919 [4029] Train's auc: 0.989757 Evaluation's auc: 0.830917 [4030] Train's auc: 0.98976 Evaluation's auc: 0.830916 [4031] Train's auc: 0.989764 Evaluation's auc: 0.830916 [4032] Train's auc: 0.989761 Evaluation's auc: 0.830911 [4033] Train's auc: 0.989763 Evaluation's auc: 0.83089 [4034] Train's auc: 0.989764 Evaluation's auc: 0.830886 [4035] Train's auc: 0.989767 Evaluation's auc: 0.830881 [4036] Train's auc: 0.989768 Evaluation's auc: 0.830879 [4037] Train's auc: 0.989768 Evaluation's auc: 0.830884 [4038] Train's auc: 0.98977 Evaluation's auc: 0.830884 [4039] Train's auc: 0.989773 Evaluation's auc: 0.830875 [4040] Train's auc: 0.989772 Evaluation's auc: 0.830868 [4041] Train's auc: 0.989773 Evaluation's auc: 0.830859 [4042] Train's auc: 0.989775 Evaluation's auc: 0.830857 [4043] Train's auc: 0.989777 Evaluation's auc: 0.830857 [4044] Train's auc: 0.989777 Evaluation's auc: 0.830832 [4045] Train's auc: 0.989778 Evaluation's auc: 0.830834 [4046] Train's auc: 0.989781 Evaluation's auc: 0.83083 [4047] Train's auc: 0.989781 Evaluation's auc: 0.830829 [4048] Train's auc: 0.989779 Evaluation's auc: 0.830831 [4049] Train's auc: 0.989777 Evaluation's auc: 0.830831 [4050] Train's auc: 0.989779 Evaluation's auc: 0.830825 [4051] Train's auc: 0.98978 Evaluation's auc: 0.830792 [4052] Train's auc: 0.989778 Evaluation's auc: 0.830794 [4053] Train's auc: 0.989778 Evaluation's auc: 0.830791 [4054] Train's auc: 0.989778 Evaluation's auc: 0.830777 [4055] Train's auc: 0.989778 Evaluation's auc: 0.830777 [4056] Train's auc: 0.989778 Evaluation's auc: 0.830777 [4057] Train's auc: 0.989778 Evaluation's auc: 0.830777 [4058] Train's auc: 0.989779 Evaluation's auc: 0.83077 [4059] Train's auc: 0.989791 Evaluation's auc: 0.830777 [4060] Train's auc: 0.989793 Evaluation's auc: 0.830782 [4061] Train's auc: 0.989795 Evaluation's auc: 0.830783 [4062] Train's auc: 0.989803 Evaluation's auc: 0.830785 [4063] Train's auc: 0.989801 Evaluation's auc: 0.830778 [4064] Train's auc: 0.989799 Evaluation's auc: 0.830785 [4065] Train's auc: 0.989801 Evaluation's auc: 0.830778 [4066] Train's auc: 0.989805 Evaluation's auc: 0.830797 [4067] Train's auc: 0.989808 Evaluation's auc: 0.830785 [4068] Train's auc: 0.989795 Evaluation's auc: 0.830792 [4069] Train's auc: 0.989795 Evaluation's auc: 0.830791 [4070] Train's auc: 0.989798 Evaluation's auc: 0.830768 [4071] Train's auc: 0.989802 Evaluation's auc: 0.830757 [4072] Train's auc: 0.989803 Evaluation's auc: 0.830758 [4073] Train's auc: 0.989811 Evaluation's auc: 0.830749 [4074] Train's auc: 0.989808 Evaluation's auc: 0.830737 [4075] Train's auc: 0.98981 Evaluation's auc: 0.830731 [4076] Train's auc: 0.989817 Evaluation's auc: 0.830714 [4077] Train's auc: 0.989817 Evaluation's auc: 0.830714 [4078] Train's auc: 0.98982 Evaluation's auc: 0.830737 [4079] Train's auc: 0.98982 Evaluation's auc: 0.830743 [4080] Train's auc: 0.989824 Evaluation's auc: 0.830776 [4081] Train's auc: 0.989839 Evaluation's auc: 0.830773 [4082] Train's auc: 0.989835 Evaluation's auc: 0.830782 [4083] Train's auc: 0.989836 Evaluation's auc: 0.830787 [4084] Train's auc: 0.989837 Evaluation's auc: 0.830765 [4085] Train's auc: 0.989841 Evaluation's auc: 0.830754 [4086] Train's auc: 0.989838 Evaluation's auc: 0.830755 [4087] Train's auc: 0.989841 Evaluation's auc: 0.830754 [4088] Train's auc: 0.989841 Evaluation's auc: 0.830783 [4089] Train's auc: 0.989845 Evaluation's auc: 0.83077 [4090] Train's auc: 0.989847 Evaluation's auc: 0.830762 [4091] Train's auc: 0.989848 Evaluation's auc: 0.830768 [4092] Train's auc: 0.989849 Evaluation's auc: 0.830758 [4093] Train's auc: 0.98985 Evaluation's auc: 0.830754 [4094] Train's auc: 0.989853 Evaluation's auc: 0.83075 [4095] Train's auc: 0.989853 Evaluation's auc: 0.830745 [4096] Train's auc: 0.989855 Evaluation's auc: 0.830729 [4097] Train's auc: 0.989851 Evaluation's auc: 0.830748 [4098] Train's auc: 0.989856 Evaluation's auc: 0.830742 [4099] Train's auc: 0.989857 Evaluation's auc: 0.830762 [4100] Train's auc: 0.989858 Evaluation's auc: 0.830761 [4101] Train's auc: 0.989859 Evaluation's auc: 0.830763 [4102] Train's auc: 0.989861 Evaluation's auc: 0.830761 [4103] Train's auc: 0.989859 Evaluation's auc: 0.830751 [4104] Train's auc: 0.989863 Evaluation's auc: 0.83074 [4105] Train's auc: 0.989863 Evaluation's auc: 0.830741 [4106] Train's auc: 0.989871 Evaluation's auc: 0.83076 [4107] Train's auc: 0.989869 Evaluation's auc: 0.830765 [4108] Train's auc: 0.989875 Evaluation's auc: 0.830757 [4109] Train's auc: 0.989879 Evaluation's auc: 0.830763 [4110] Train's auc: 0.989881 Evaluation's auc: 0.830747 [4111] Train's auc: 0.989884 Evaluation's auc: 0.830762 [4112] Train's auc: 0.989889 Evaluation's auc: 0.830777 [4113] Train's auc: 0.989889 Evaluation's auc: 0.830763 [4114] Train's auc: 0.989894 Evaluation's auc: 0.83076 [4115] Train's auc: 0.989893 Evaluation's auc: 0.830758 [4116] Train's auc: 0.989896 Evaluation's auc: 0.830748 [4117] Train's auc: 0.989896 Evaluation's auc: 0.830743 [4118] Train's auc: 0.989896 Evaluation's auc: 0.830736 [4119] Train's auc: 0.989902 Evaluation's auc: 0.830752 [4120] Train's auc: 0.989915 Evaluation's auc: 0.83074 [4121] Train's auc: 0.989915 Evaluation's auc: 0.83074 [4122] Train's auc: 0.989915 Evaluation's auc: 0.830766 [4123] Train's auc: 0.989922 Evaluation's auc: 0.830767 [4124] Train's auc: 0.989922 Evaluation's auc: 0.830755 [4125] Train's auc: 0.989927 Evaluation's auc: 0.830753 [4126] Train's auc: 0.989927 Evaluation's auc: 0.830753 [4127] Train's auc: 0.989931 Evaluation's auc: 0.83075 [4128] Train's auc: 0.989932 Evaluation's auc: 0.830756 [4129] Train's auc: 0.989932 Evaluation's auc: 0.830754 [4130] Train's auc: 0.989934 Evaluation's auc: 0.830749 [4131] Train's auc: 0.989933 Evaluation's auc: 0.830726 [4132] Train's auc: 0.989933 Evaluation's auc: 0.830714 [4133] Train's auc: 0.98993 Evaluation's auc: 0.830727 [4134] Train's auc: 0.989933 Evaluation's auc: 0.830724 [4135] Train's auc: 0.989929 Evaluation's auc: 0.830722 [4136] Train's auc: 0.989934 Evaluation's auc: 0.830695 [4137] Train's auc: 0.989937 Evaluation's auc: 0.830689 [4138] Train's auc: 0.989942 Evaluation's auc: 0.830678 [4139] Train's auc: 0.989942 Evaluation's auc: 0.830675 [4140] Train's auc: 0.989945 Evaluation's auc: 0.830695 [4141] Train's auc: 0.989945 Evaluation's auc: 0.830696 [4142] Train's auc: 0.989946 Evaluation's auc: 0.830676 [4143] Train's auc: 0.989953 Evaluation's auc: 0.83066 [4144] Train's auc: 0.989955 Evaluation's auc: 0.830638 [4145] Train's auc: 0.989963 Evaluation's auc: 0.830628 [4146] Train's auc: 0.989959 Evaluation's auc: 0.83064 [4147] Train's auc: 0.98996 Evaluation's auc: 0.830632 [4148] Train's auc: 0.989965 Evaluation's auc: 0.830625 [4149] Train's auc: 0.989968 Evaluation's auc: 0.830604 [4150] Train's auc: 0.98997 Evaluation's auc: 0.830622 [4151] Train's auc: 0.989977 Evaluation's auc: 0.830619 [4152] Train's auc: 0.989978 Evaluation's auc: 0.830615 [4153] Train's auc: 0.989978 Evaluation's auc: 0.830626 [4154] Train's auc: 0.989979 Evaluation's auc: 0.830627 [4155] Train's auc: 0.989983 Evaluation's auc: 0.830617 [4156] Train's auc: 0.989985 Evaluation's auc: 0.830614 [4157] Train's auc: 0.989986 Evaluation's auc: 0.830608 [4158] Train's auc: 0.989993 Evaluation's auc: 0.830622 [4159] Train's auc: 0.989991 Evaluation's auc: 0.830619 [4160] Train's auc: 0.990001 Evaluation's auc: 0.830626 [4161] Train's auc: 0.990004 Evaluation's auc: 0.830629 [4162] Train's auc: 0.990003 Evaluation's auc: 0.830631 [4163] Train's auc: 0.990004 Evaluation's auc: 0.830638 [4164] Train's auc: 0.990004 Evaluation's auc: 0.830623 [4165] Train's auc: 0.99 Evaluation's auc: 0.830625 [4166] Train's auc: 0.990001 Evaluation's auc: 0.830597 [4167] Train's auc: 0.990001 Evaluation's auc: 0.830597 [4168] Train's auc: 0.99 Evaluation's auc: 0.830595 [4169] Train's auc: 0.989996 Evaluation's auc: 0.830591 [4170] Train's auc: 0.989998 Evaluation's auc: 0.830569 [4171] Train's auc: 0.989997 Evaluation's auc: 0.830588 [4172] Train's auc: 0.990001 Evaluation's auc: 0.830579 [4173] Train's auc: 0.990001 Evaluation's auc: 0.830579 [4174] Train's auc: 0.990001 Evaluation's auc: 0.830585 [4175] Train's auc: 0.990004 Evaluation's auc: 0.830595 [4176] Train's auc: 0.990006 Evaluation's auc: 0.830585 [4177] Train's auc: 0.990014 Evaluation's auc: 0.830574 [4178] Train's auc: 0.990015 Evaluation's auc: 0.830574 [4179] Train's auc: 0.990015 Evaluation's auc: 0.830568 [4180] Train's auc: 0.990017 Evaluation's auc: 0.830563 [4181] Train's auc: 0.990018 Evaluation's auc: 0.83057 [4182] Train's auc: 0.990023 Evaluation's auc: 0.830579 [4183] Train's auc: 0.990019 Evaluation's auc: 0.830581 [4184] Train's auc: 0.990021 Evaluation's auc: 0.83058 [4185] Train's auc: 0.990021 Evaluation's auc: 0.830579 [4186] Train's auc: 0.990019 Evaluation's auc: 0.830592 [4187] Train's auc: 0.990018 Evaluation's auc: 0.830593 [4188] Train's auc: 0.99002 Evaluation's auc: 0.830599 [4189] Train's auc: 0.990022 Evaluation's auc: 0.83061 [4190] Train's auc: 0.990026 Evaluation's auc: 0.830594 [4191] Train's auc: 0.990028 Evaluation's auc: 0.830595 [4192] Train's auc: 0.990031 Evaluation's auc: 0.830595 [4193] Train's auc: 0.990031 Evaluation's auc: 0.830597 [4194] Train's auc: 0.990036 Evaluation's auc: 0.830587 [4195] Train's auc: 0.990033 Evaluation's auc: 0.830586 [4196] Train's auc: 0.990033 Evaluation's auc: 0.830585 [4197] Train's auc: 0.990036 Evaluation's auc: 0.830576 [4198] Train's auc: 0.990042 Evaluation's auc: 0.830565 [4199] Train's auc: 0.990044 Evaluation's auc: 0.830559 [4200] Train's auc: 0.990051 Evaluation's auc: 0.830565 [4201] Train's auc: 0.990052 Evaluation's auc: 0.830562 [4202] Train's auc: 0.990055 Evaluation's auc: 0.830559 [4203] Train's auc: 0.990055 Evaluation's auc: 0.830573 [4204] Train's auc: 0.990055 Evaluation's auc: 0.830573 [4205] Train's auc: 0.990054 Evaluation's auc: 0.830574 [4206] Train's auc: 0.990054 Evaluation's auc: 0.830564 [4207] Train's auc: 0.990056 Evaluation's auc: 0.830566 [4208] Train's auc: 0.990056 Evaluation's auc: 0.830566 [4209] Train's auc: 0.990057 Evaluation's auc: 0.83058 [4210] Train's auc: 0.990057 Evaluation's auc: 0.83058 [4211] Train's auc: 0.990057 Evaluation's auc: 0.83058 [4212] Train's auc: 0.990059 Evaluation's auc: 0.830568 [4213] Train's auc: 0.990059 Evaluation's auc: 0.830568 [4214] Train's auc: 0.99006 Evaluation's auc: 0.830565 [4215] Train's auc: 0.990064 Evaluation's auc: 0.830576 [4216] Train's auc: 0.990065 Evaluation's auc: 0.83056 [4217] Train's auc: 0.990066 Evaluation's auc: 0.830553 [4218] Train's auc: 0.990066 Evaluation's auc: 0.830551 [4219] Train's auc: 0.99007 Evaluation's auc: 0.830556 [4220] Train's auc: 0.990073 Evaluation's auc: 0.830554 [4221] Train's auc: 0.990071 Evaluation's auc: 0.830551 [4222] Train's auc: 0.990071 Evaluation's auc: 0.830545 [4223] Train's auc: 0.990071 Evaluation's auc: 0.830545 [4224] Train's auc: 0.990071 Evaluation's auc: 0.830545 [4225] Train's auc: 0.990071 Evaluation's auc: 0.830545 [4226] Train's auc: 0.990072 Evaluation's auc: 0.830545 [4227] Train's auc: 0.990072 Evaluation's auc: 0.830544 [4228] Train's auc: 0.990072 Evaluation's auc: 0.830543 [4229] Train's auc: 0.990072 Evaluation's auc: 0.830544 [4230] Train's auc: 0.990078 Evaluation's auc: 0.830541 [4231] Train's auc: 0.990079 Evaluation's auc: 0.830547 [4232] Train's auc: 0.990079 Evaluation's auc: 0.830547 [4233] Train's auc: 0.990079 Evaluation's auc: 0.830547 [4234] Train's auc: 0.99008 Evaluation's auc: 0.830542 [4235] Train's auc: 0.99008 Evaluation's auc: 0.830542 [4236] Train's auc: 0.990084 Evaluation's auc: 0.830539 [4237] Train's auc: 0.990087 Evaluation's auc: 0.830528 [4238] Train's auc: 0.990089 Evaluation's auc: 0.830531 [4239] Train's auc: 0.99009 Evaluation's auc: 0.830554 [4240] Train's auc: 0.990091 Evaluation's auc: 0.830552 [4241] Train's auc: 0.990094 Evaluation's auc: 0.830542 [4242] Train's auc: 0.990095 Evaluation's auc: 0.830525 [4243] Train's auc: 0.990097 Evaluation's auc: 0.830526 [4244] Train's auc: 0.990097 Evaluation's auc: 0.830528 [4245] Train's auc: 0.990098 Evaluation's auc: 0.830536 [4246] Train's auc: 0.990103 Evaluation's auc: 0.830532 [4247] Train's auc: 0.990103 Evaluation's auc: 0.830532 [4248] Train's auc: 0.990103 Evaluation's auc: 0.830534 [4249] Train's auc: 0.990111 Evaluation's auc: 0.830524 [4250] Train's auc: 0.99011 Evaluation's auc: 0.830518 [4251] Train's auc: 0.990107 Evaluation's auc: 0.830533 [4252] Train's auc: 0.990104 Evaluation's auc: 0.830545 [4253] Train's auc: 0.990107 Evaluation's auc: 0.83054 [4254] Train's auc: 0.990114 Evaluation's auc: 0.830529 [4255] Train's auc: 0.990121 Evaluation's auc: 0.830519 [4256] Train's auc: 0.990121 Evaluation's auc: 0.830519 [4257] Train's auc: 0.990126 Evaluation's auc: 0.830514 [4258] Train's auc: 0.990126 Evaluation's auc: 0.830514 [4259] Train's auc: 0.990131 Evaluation's auc: 0.830518 [4260] Train's auc: 0.990132 Evaluation's auc: 0.830526 [4261] Train's auc: 0.990132 Evaluation's auc: 0.830526 [4262] Train's auc: 0.990136 Evaluation's auc: 0.83051 [4263] Train's auc: 0.990146 Evaluation's auc: 0.830506 [4264] Train's auc: 0.990147 Evaluation's auc: 0.830507 [4265] Train's auc: 0.990142 Evaluation's auc: 0.83051 [4266] Train's auc: 0.990139 Evaluation's auc: 0.830505 [4267] Train's auc: 0.990142 Evaluation's auc: 0.830508 [4268] Train's auc: 0.990141 Evaluation's auc: 0.830512 [4269] Train's auc: 0.990143 Evaluation's auc: 0.830495 [4270] Train's auc: 0.990144 Evaluation's auc: 0.830486 [4271] Train's auc: 0.990147 Evaluation's auc: 0.830484 [4272] Train's auc: 0.990148 Evaluation's auc: 0.830477 [4273] Train's auc: 0.990149 Evaluation's auc: 0.830466 [4274] Train's auc: 0.990151 Evaluation's auc: 0.83047 [4275] Train's auc: 0.990152 Evaluation's auc: 0.830467 [4276] Train's auc: 0.990157 Evaluation's auc: 0.830459 [4277] Train's auc: 0.990161 Evaluation's auc: 0.830468 [4278] Train's auc: 0.990167 Evaluation's auc: 0.830483 [4279] Train's auc: 0.990168 Evaluation's auc: 0.830462 [4280] Train's auc: 0.990167 Evaluation's auc: 0.830462 [4281] Train's auc: 0.990169 Evaluation's auc: 0.830461 [4282] Train's auc: 0.990171 Evaluation's auc: 0.830461 [4283] Train's auc: 0.990174 Evaluation's auc: 0.830456 [4284] Train's auc: 0.99018 Evaluation's auc: 0.830468 [4285] Train's auc: 0.990186 Evaluation's auc: 0.83046 [4286] Train's auc: 0.990188 Evaluation's auc: 0.830476 [4287] Train's auc: 0.990187 Evaluation's auc: 0.830494 [4288] Train's auc: 0.990188 Evaluation's auc: 0.8305 [4289] Train's auc: 0.990192 Evaluation's auc: 0.8305 [4290] Train's auc: 0.990191 Evaluation's auc: 0.8305 [4291] Train's auc: 0.990191 Evaluation's auc: 0.830495 [4292] Train's auc: 0.990192 Evaluation's auc: 0.83051 [4293] Train's auc: 0.990192 Evaluation's auc: 0.830521 [4294] Train's auc: 0.990193 Evaluation's auc: 0.830519 [4295] Train's auc: 0.990195 Evaluation's auc: 0.830507 [4296] Train's auc: 0.990194 Evaluation's auc: 0.830506 [4297] Train's auc: 0.990194 Evaluation's auc: 0.830502 [4298] Train's auc: 0.990197 Evaluation's auc: 0.83051 [4299] Train's auc: 0.990201 Evaluation's auc: 0.8305 [4300] Train's auc: 0.990202 Evaluation's auc: 0.830519 [4301] Train's auc: 0.990203 Evaluation's auc: 0.830519 [4302] Train's auc: 0.990205 Evaluation's auc: 0.830516 [4303] Train's auc: 0.990205 Evaluation's auc: 0.830516 [4304] Train's auc: 0.990206 Evaluation's auc: 0.830515 [4305] Train's auc: 0.990206 Evaluation's auc: 0.830515 [4306] Train's auc: 0.990205 Evaluation's auc: 0.830516 [4307] Train's auc: 0.990205 Evaluation's auc: 0.830516 [4308] Train's auc: 0.990204 Evaluation's auc: 0.830516 [4309] Train's auc: 0.990204 Evaluation's auc: 0.830516 [4310] Train's auc: 0.990204 Evaluation's auc: 0.830517 [4311] Train's auc: 0.990204 Evaluation's auc: 0.830514 [4312] Train's auc: 0.990203 Evaluation's auc: 0.830517 [4313] Train's auc: 0.990203 Evaluation's auc: 0.830517 [4314] Train's auc: 0.990203 Evaluation's auc: 0.830517 [4315] Train's auc: 0.990205 Evaluation's auc: 0.830506 [4316] Train's auc: 0.990219 Evaluation's auc: 0.830501 [4317] Train's auc: 0.99022 Evaluation's auc: 0.830501 [4318] Train's auc: 0.990221 Evaluation's auc: 0.8305 [4319] Train's auc: 0.990221 Evaluation's auc: 0.8305 [4320] Train's auc: 0.990224 Evaluation's auc: 0.830488 [4321] Train's auc: 0.990224 Evaluation's auc: 0.830487 [4322] Train's auc: 0.990224 Evaluation's auc: 0.830487 [4323] Train's auc: 0.990223 Evaluation's auc: 0.830485 [4324] Train's auc: 0.990224 Evaluation's auc: 0.830474 [4325] Train's auc: 0.990228 Evaluation's auc: 0.830452 [4326] Train's auc: 0.990228 Evaluation's auc: 0.830452 [4327] Train's auc: 0.990228 Evaluation's auc: 0.830467 [4328] Train's auc: 0.990231 Evaluation's auc: 0.830457 [4329] Train's auc: 0.990231 Evaluation's auc: 0.830456 [4330] Train's auc: 0.990231 Evaluation's auc: 0.830456 [4331] Train's auc: 0.990232 Evaluation's auc: 0.830455 [4332] Train's auc: 0.990232 Evaluation's auc: 0.830455 [4333] Train's auc: 0.990232 Evaluation's auc: 0.830455 [4334] Train's auc: 0.990232 Evaluation's auc: 0.830455 [4335] Train's auc: 0.990232 Evaluation's auc: 0.830455 [4336] Train's auc: 0.990232 Evaluation's auc: 0.830455 [4337] Train's auc: 0.990232 Evaluation's auc: 0.830455 [4338] Train's auc: 0.990232 Evaluation's auc: 0.830455 [4339] Train's auc: 0.990232 Evaluation's auc: 0.830455 [4340] Train's auc: 0.990232 Evaluation's auc: 0.830455 [4341] Train's auc: 0.990234 Evaluation's auc: 0.830446 [4342] Train's auc: 0.990234 Evaluation's auc: 0.830446 [4343] Train's auc: 0.990234 Evaluation's auc: 0.830445 [4344] Train's auc: 0.990234 Evaluation's auc: 0.830445 [4345] Train's auc: 0.990234 Evaluation's auc: 0.830447 [4346] Train's auc: 0.990234 Evaluation's auc: 0.830448 [4347] Train's auc: 0.990234 Evaluation's auc: 0.830448 [4348] Train's auc: 0.990234 Evaluation's auc: 0.830448 [4349] Train's auc: 0.990234 Evaluation's auc: 0.830448 [4350] Train's auc: 0.990234 Evaluation's auc: 0.830448 [4351] Train's auc: 0.990234 Evaluation's auc: 0.830448 [4352] Train's auc: 0.990234 Evaluation's auc: 0.830448 [4353] Train's auc: 0.990234 Evaluation's auc: 0.830459 [4354] Train's auc: 0.990239 Evaluation's auc: 0.830425 [4355] Train's auc: 0.990239 Evaluation's auc: 0.830425 [4356] Train's auc: 0.990239 Evaluation's auc: 0.830426 [4357] Train's auc: 0.990239 Evaluation's auc: 0.830436 [4358] Train's auc: 0.99024 Evaluation's auc: 0.830434 [4359] Train's auc: 0.990243 Evaluation's auc: 0.830425 [4360] Train's auc: 0.990244 Evaluation's auc: 0.830415 [4361] Train's auc: 0.990244 Evaluation's auc: 0.830415 [4362] Train's auc: 0.990244 Evaluation's auc: 0.830415 [4363] Train's auc: 0.990244 Evaluation's auc: 0.830416 [4364] Train's auc: 0.990244 Evaluation's auc: 0.830416 [4365] Train's auc: 0.990244 Evaluation's auc: 0.830421 [4366] Train's auc: 0.990244 Evaluation's auc: 0.830421 [4367] Train's auc: 0.990244 Evaluation's auc: 0.830421 [4368] Train's auc: 0.990244 Evaluation's auc: 0.830421 [4369] Train's auc: 0.990244 Evaluation's auc: 0.830421 [4370] Train's auc: 0.990244 Evaluation's auc: 0.830421 [4371] Train's auc: 0.990244 Evaluation's auc: 0.830423 [4372] Train's auc: 0.990244 Evaluation's auc: 0.830423 [4373] Train's auc: 0.990244 Evaluation's auc: 0.830423 [4374] Train's auc: 0.990244 Evaluation's auc: 0.830424 [4375] Train's auc: 0.990243 Evaluation's auc: 0.830424 [4376] Train's auc: 0.990243 Evaluation's auc: 0.830424 [4377] Train's auc: 0.990243 Evaluation's auc: 0.830422 [4378] Train's auc: 0.990243 Evaluation's auc: 0.830422 [4379] Train's auc: 0.990243 Evaluation's auc: 0.830422 [4380] Train's auc: 0.990243 Evaluation's auc: 0.830422 [4381] Train's auc: 0.990243 Evaluation's auc: 0.830423 [4382] Train's auc: 0.990244 Evaluation's auc: 0.830451 [4383] Train's auc: 0.990252 Evaluation's auc: 0.830471 [4384] Train's auc: 0.990251 Evaluation's auc: 0.830471 [4385] Train's auc: 0.990255 Evaluation's auc: 0.830471 [4386] Train's auc: 0.990255 Evaluation's auc: 0.830463 [4387] Train's auc: 0.990259 Evaluation's auc: 0.830451 [4388] Train's auc: 0.990257 Evaluation's auc: 0.830452 [4389] Train's auc: 0.990262 Evaluation's auc: 0.830448 [4390] Train's auc: 0.99026 Evaluation's auc: 0.830447 [4391] Train's auc: 0.99026 Evaluation's auc: 0.830442 [4392] Train's auc: 0.990261 Evaluation's auc: 0.830424 [4393] Train's auc: 0.990263 Evaluation's auc: 0.830438 [4394] Train's auc: 0.990261 Evaluation's auc: 0.830434 [4395] Train's auc: 0.990264 Evaluation's auc: 0.830431 [4396] Train's auc: 0.990267 Evaluation's auc: 0.830428 [4397] Train's auc: 0.990267 Evaluation's auc: 0.830429 [4398] Train's auc: 0.990265 Evaluation's auc: 0.830433 [4399] Train's auc: 0.990269 Evaluation's auc: 0.830429 [4400] Train's auc: 0.990276 Evaluation's auc: 0.83046 [4401] Train's auc: 0.990276 Evaluation's auc: 0.83047 [4402] Train's auc: 0.990275 Evaluation's auc: 0.830476 [4403] Train's auc: 0.990276 Evaluation's auc: 0.830473 [4404] Train's auc: 0.990276 Evaluation's auc: 0.830473 [4405] Train's auc: 0.990275 Evaluation's auc: 0.830474 [4406] Train's auc: 0.990275 Evaluation's auc: 0.830474 [4407] Train's auc: 0.990275 Evaluation's auc: 0.830474 [4408] Train's auc: 0.990275 Evaluation's auc: 0.830471 [4409] Train's auc: 0.990278 Evaluation's auc: 0.830465 [4410] Train's auc: 0.990276 Evaluation's auc: 0.830465 [4411] Train's auc: 0.990277 Evaluation's auc: 0.830467 [4412] Train's auc: 0.99028 Evaluation's auc: 0.830481 [4413] Train's auc: 0.990288 Evaluation's auc: 0.830467 [4414] Train's auc: 0.99029 Evaluation's auc: 0.830464 [4415] Train's auc: 0.990295 Evaluation's auc: 0.830472 [4416] Train's auc: 0.990296 Evaluation's auc: 0.830467 [4417] Train's auc: 0.990297 Evaluation's auc: 0.830477 [4418] Train's auc: 0.990298 Evaluation's auc: 0.8305 [4419] Train's auc: 0.990299 Evaluation's auc: 0.830487 [4420] Train's auc: 0.990303 Evaluation's auc: 0.830483 [4421] Train's auc: 0.990304 Evaluation's auc: 0.830482 [4422] Train's auc: 0.990305 Evaluation's auc: 0.830485 [4423] Train's auc: 0.990306 Evaluation's auc: 0.830482 [4424] Train's auc: 0.990306 Evaluation's auc: 0.830482 [4425] Train's auc: 0.990306 Evaluation's auc: 0.830483 [4426] Train's auc: 0.990308 Evaluation's auc: 0.830474 [4427] Train's auc: 0.990309 Evaluation's auc: 0.830481 [4428] Train's auc: 0.990311 Evaluation's auc: 0.830469 [4429] Train's auc: 0.990312 Evaluation's auc: 0.830491 [4430] Train's auc: 0.990312 Evaluation's auc: 0.830489 [4431] Train's auc: 0.990312 Evaluation's auc: 0.830487 [4432] Train's auc: 0.990313 Evaluation's auc: 0.830488 [4433] Train's auc: 0.990314 Evaluation's auc: 0.830482 [4434] Train's auc: 0.99032 Evaluation's auc: 0.830472 [4435] Train's auc: 0.990325 Evaluation's auc: 0.830451 [4436] Train's auc: 0.99033 Evaluation's auc: 0.830475 [4437] Train's auc: 0.990331 Evaluation's auc: 0.830485 [4438] Train's auc: 0.990331 Evaluation's auc: 0.830481 [4439] Train's auc: 0.99033 Evaluation's auc: 0.830469 [4440] Train's auc: 0.99033 Evaluation's auc: 0.830448 [4441] Train's auc: 0.990332 Evaluation's auc: 0.830443 [4442] Train's auc: 0.990337 Evaluation's auc: 0.830442 [4443] Train's auc: 0.990336 Evaluation's auc: 0.830443 [4444] Train's auc: 0.990337 Evaluation's auc: 0.830443 [4445] Train's auc: 0.990339 Evaluation's auc: 0.83045 [4446] Train's auc: 0.990331 Evaluation's auc: 0.830447 [4447] Train's auc: 0.990335 Evaluation's auc: 0.830422 [4448] Train's auc: 0.990351 Evaluation's auc: 0.830408 [4449] Train's auc: 0.990353 Evaluation's auc: 0.830412 [4450] Train's auc: 0.990353 Evaluation's auc: 0.830413 [4451] Train's auc: 0.990356 Evaluation's auc: 0.830415 [4452] Train's auc: 0.990356 Evaluation's auc: 0.830408 [4453] Train's auc: 0.990368 Evaluation's auc: 0.830422 [4454] Train's auc: 0.990368 Evaluation's auc: 0.830404 [4455] Train's auc: 0.990373 Evaluation's auc: 0.830408 [4456] Train's auc: 0.990373 Evaluation's auc: 0.830382 [4457] Train's auc: 0.990376 Evaluation's auc: 0.830389 [4458] Train's auc: 0.990377 Evaluation's auc: 0.830388 [4459] Train's auc: 0.99038 Evaluation's auc: 0.830384 [4460] Train's auc: 0.990381 Evaluation's auc: 0.830385 [4461] Train's auc: 0.99038 Evaluation's auc: 0.830367 [4462] Train's auc: 0.990381 Evaluation's auc: 0.830382 [4463] Train's auc: 0.990382 Evaluation's auc: 0.830367 [4464] Train's auc: 0.990384 Evaluation's auc: 0.830374 [4465] Train's auc: 0.990384 Evaluation's auc: 0.83037 [4466] Train's auc: 0.990384 Evaluation's auc: 0.830368 [4467] Train's auc: 0.990387 Evaluation's auc: 0.830367 [4468] Train's auc: 0.990387 Evaluation's auc: 0.830367 [4469] Train's auc: 0.990388 Evaluation's auc: 0.830355 [4470] Train's auc: 0.990388 Evaluation's auc: 0.830355 [4471] Train's auc: 0.990388 Evaluation's auc: 0.830355 [4472] Train's auc: 0.990388 Evaluation's auc: 0.830356 [4473] Train's auc: 0.990388 Evaluation's auc: 0.830355 [4474] Train's auc: 0.990388 Evaluation's auc: 0.830376 [4475] Train's auc: 0.990387 Evaluation's auc: 0.830376 [4476] Train's auc: 0.990382 Evaluation's auc: 0.830379 [4477] Train's auc: 0.990385 Evaluation's auc: 0.830377 [4478] Train's auc: 0.990386 Evaluation's auc: 0.830374 [4479] Train's auc: 0.990387 Evaluation's auc: 0.830374 [4480] Train's auc: 0.990389 Evaluation's auc: 0.830372 [4481] Train's auc: 0.990389 Evaluation's auc: 0.830373 [4482] Train's auc: 0.990389 Evaluation's auc: 0.830373 [4483] Train's auc: 0.990389 Evaluation's auc: 0.830366 [4484] Train's auc: 0.990393 Evaluation's auc: 0.830367 [4485] Train's auc: 0.990394 Evaluation's auc: 0.830372 [4486] Train's auc: 0.990393 Evaluation's auc: 0.830373 [4487] Train's auc: 0.990397 Evaluation's auc: 0.830388 [4488] Train's auc: 0.990398 Evaluation's auc: 0.830382 [4489] Train's auc: 0.990398 Evaluation's auc: 0.830382 [4490] Train's auc: 0.990398 Evaluation's auc: 0.830382 [4491] Train's auc: 0.990395 Evaluation's auc: 0.830391 [4492] Train's auc: 0.990395 Evaluation's auc: 0.830391 [4493] Train's auc: 0.990399 Evaluation's auc: 0.830398 [4494] Train's auc: 0.990399 Evaluation's auc: 0.830398 [4495] Train's auc: 0.990399 Evaluation's auc: 0.830398 [4496] Train's auc: 0.990399 Evaluation's auc: 0.830398 [4497] Train's auc: 0.990399 Evaluation's auc: 0.830403 [4498] Train's auc: 0.990401 Evaluation's auc: 0.830414 [4499] Train's auc: 0.990406 Evaluation's auc: 0.830397 [4500] Train's auc: 0.990406 Evaluation's auc: 0.830397 [4501] Train's auc: 0.990408 Evaluation's auc: 0.830413 [4502] Train's auc: 0.990409 Evaluation's auc: 0.830406 [4503] Train's auc: 0.990409 Evaluation's auc: 0.830406 [4504] Train's auc: 0.990409 Evaluation's auc: 0.830406 [4505] Train's auc: 0.990409 Evaluation's auc: 0.830406 [4506] Train's auc: 0.990409 Evaluation's auc: 0.830406 [4507] Train's auc: 0.990409 Evaluation's auc: 0.830406 [4508] Train's auc: 0.990409 Evaluation's auc: 0.830406 [4509] Train's auc: 0.990409 Evaluation's auc: 0.830406 [4510] Train's auc: 0.990409 Evaluation's auc: 0.830396 [4511] Train's auc: 0.990403 Evaluation's auc: 0.830421 [4512] Train's auc: 0.990404 Evaluation's auc: 0.830421 [4513] Train's auc: 0.990402 Evaluation's auc: 0.830427 [4514] Train's auc: 0.990402 Evaluation's auc: 0.830427 [4515] Train's auc: 0.990403 Evaluation's auc: 0.830428 [4516] Train's auc: 0.990404 Evaluation's auc: 0.830448 [4517] Train's auc: 0.990406 Evaluation's auc: 0.830448 [4518] Train's auc: 0.990407 Evaluation's auc: 0.830441 [4519] Train's auc: 0.990413 Evaluation's auc: 0.83043 [4520] Train's auc: 0.990413 Evaluation's auc: 0.830427 [4521] Train's auc: 0.990411 Evaluation's auc: 0.83042 [4522] Train's auc: 0.990411 Evaluation's auc: 0.83042 [4523] Train's auc: 0.990411 Evaluation's auc: 0.83042 [4524] Train's auc: 0.990413 Evaluation's auc: 0.830423 [4525] Train's auc: 0.990411 Evaluation's auc: 0.830428 [4526] Train's auc: 0.990422 Evaluation's auc: 0.830402 [4527] Train's auc: 0.990425 Evaluation's auc: 0.830395 [4528] Train's auc: 0.990433 Evaluation's auc: 0.830373 [4529] Train's auc: 0.990435 Evaluation's auc: 0.830344 [4530] Train's auc: 0.990437 Evaluation's auc: 0.830345 [4531] Train's auc: 0.990438 Evaluation's auc: 0.830365 [4532] Train's auc: 0.990438 Evaluation's auc: 0.830348 [4533] Train's auc: 0.990441 Evaluation's auc: 0.830365 [4534] Train's auc: 0.99044 Evaluation's auc: 0.830379 [4535] Train's auc: 0.990441 Evaluation's auc: 0.830364 [4536] Train's auc: 0.99044 Evaluation's auc: 0.830364 [4537] Train's auc: 0.99044 Evaluation's auc: 0.830364 [4538] Train's auc: 0.99044 Evaluation's auc: 0.830364 [4539] Train's auc: 0.990441 Evaluation's auc: 0.830381 [4540] Train's auc: 0.990444 Evaluation's auc: 0.830368 [4541] Train's auc: 0.990447 Evaluation's auc: 0.830356 [4542] Train's auc: 0.990448 Evaluation's auc: 0.830363 [4543] Train's auc: 0.990447 Evaluation's auc: 0.83038 [4544] Train's auc: 0.990448 Evaluation's auc: 0.830372 [4545] Train's auc: 0.990449 Evaluation's auc: 0.830373 [4546] Train's auc: 0.990449 Evaluation's auc: 0.830374 [4547] Train's auc: 0.990453 Evaluation's auc: 0.830372 [4548] Train's auc: 0.990454 Evaluation's auc: 0.830384 [4549] Train's auc: 0.990455 Evaluation's auc: 0.830376 [4550] Train's auc: 0.990455 Evaluation's auc: 0.830369 [4551] Train's auc: 0.990455 Evaluation's auc: 0.830369 [4552] Train's auc: 0.990464 Evaluation's auc: 0.830366 [4553] Train's auc: 0.990466 Evaluation's auc: 0.830359 [4554] Train's auc: 0.990466 Evaluation's auc: 0.830372 [4555] Train's auc: 0.990465 Evaluation's auc: 0.830374 [4556] Train's auc: 0.99047 Evaluation's auc: 0.830367 [4557] Train's auc: 0.99047 Evaluation's auc: 0.830367 [4558] Train's auc: 0.990469 Evaluation's auc: 0.830367 [4559] Train's auc: 0.990469 Evaluation's auc: 0.830368 [4560] Train's auc: 0.990469 Evaluation's auc: 0.830366 [4561] Train's auc: 0.990469 Evaluation's auc: 0.830366 [4562] Train's auc: 0.990469 Evaluation's auc: 0.830366 [4563] Train's auc: 0.990469 Evaluation's auc: 0.830366 [4564] Train's auc: 0.990469 Evaluation's auc: 0.830367 [4565] Train's auc: 0.99047 Evaluation's auc: 0.830365 [4566] Train's auc: 0.990472 Evaluation's auc: 0.830343 [4567] Train's auc: 0.990476 Evaluation's auc: 0.830339 [4568] Train's auc: 0.990477 Evaluation's auc: 0.830346 [4569] Train's auc: 0.990479 Evaluation's auc: 0.830324 [4570] Train's auc: 0.990482 Evaluation's auc: 0.830293 [4571] Train's auc: 0.99048 Evaluation's auc: 0.830306 [4572] Train's auc: 0.990483 Evaluation's auc: 0.830285 [4573] Train's auc: 0.990484 Evaluation's auc: 0.830288 [4574] Train's auc: 0.990487 Evaluation's auc: 0.830278 [4575] Train's auc: 0.990492 Evaluation's auc: 0.830268 [4576] Train's auc: 0.990495 Evaluation's auc: 0.83026 [4577] Train's auc: 0.9905 Evaluation's auc: 0.830268 [4578] Train's auc: 0.990502 Evaluation's auc: 0.830248 [4579] Train's auc: 0.990502 Evaluation's auc: 0.83024 [4580] Train's auc: 0.990504 Evaluation's auc: 0.830244 [4581] Train's auc: 0.990506 Evaluation's auc: 0.830261 [4582] Train's auc: 0.990509 Evaluation's auc: 0.830259 [4583] Train's auc: 0.99051 Evaluation's auc: 0.830257 [4584] Train's auc: 0.990513 Evaluation's auc: 0.830254 [4585] Train's auc: 0.990511 Evaluation's auc: 0.830263 [4586] Train's auc: 0.990511 Evaluation's auc: 0.830257 [4587] Train's auc: 0.990523 Evaluation's auc: 0.830267 [4588] Train's auc: 0.990523 Evaluation's auc: 0.830265 [4589] Train's auc: 0.990524 Evaluation's auc: 0.830258 [4590] Train's auc: 0.990525 Evaluation's auc: 0.830244 [4591] Train's auc: 0.990525 Evaluation's auc: 0.830244 [4592] Train's auc: 0.990527 Evaluation's auc: 0.830234 [4593] Train's auc: 0.990527 Evaluation's auc: 0.830234 [4594] Train's auc: 0.990529 Evaluation's auc: 0.830225 [4595] Train's auc: 0.99053 Evaluation's auc: 0.830225 [4596] Train's auc: 0.990528 Evaluation's auc: 0.83022 [4597] Train's auc: 0.990528 Evaluation's auc: 0.830223 [4598] Train's auc: 0.99053 Evaluation's auc: 0.830229 [4599] Train's auc: 0.99053 Evaluation's auc: 0.830232 [4600] Train's auc: 0.990532 Evaluation's auc: 0.830223 [4601] Train's auc: 0.990534 Evaluation's auc: 0.830217 [4602] Train's auc: 0.990534 Evaluation's auc: 0.830223 [4603] Train's auc: 0.990533 Evaluation's auc: 0.830219 [4604] Train's auc: 0.990536 Evaluation's auc: 0.830206 [4605] Train's auc: 0.990536 Evaluation's auc: 0.830207 [4606] Train's auc: 0.990536 Evaluation's auc: 0.830211 [4607] Train's auc: 0.990536 Evaluation's auc: 0.830211 [4608] Train's auc: 0.990538 Evaluation's auc: 0.830224 [4609] Train's auc: 0.99054 Evaluation's auc: 0.830224 [4610] Train's auc: 0.990542 Evaluation's auc: 0.83022 [4611] Train's auc: 0.990546 Evaluation's auc: 0.83021 [4612] Train's auc: 0.990548 Evaluation's auc: 0.830195 [4613] Train's auc: 0.990551 Evaluation's auc: 0.830194 [4614] Train's auc: 0.990554 Evaluation's auc: 0.830192 [4615] Train's auc: 0.990553 Evaluation's auc: 0.830192 [4616] Train's auc: 0.990554 Evaluation's auc: 0.83021 [4617] Train's auc: 0.990554 Evaluation's auc: 0.83021 [4618] Train's auc: 0.990554 Evaluation's auc: 0.830215 [4619] Train's auc: 0.99056 Evaluation's auc: 0.830213 [4620] Train's auc: 0.990559 Evaluation's auc: 0.830212 [4621] Train's auc: 0.99056 Evaluation's auc: 0.830208 [4622] Train's auc: 0.990561 Evaluation's auc: 0.830209 [4623] Train's auc: 0.990561 Evaluation's auc: 0.830207 [4624] Train's auc: 0.990561 Evaluation's auc: 0.830207 [4625] Train's auc: 0.990561 Evaluation's auc: 0.830207 [4626] Train's auc: 0.990561 Evaluation's auc: 0.830207 [4627] Train's auc: 0.990561 Evaluation's auc: 0.830207 [4628] Train's auc: 0.990561 Evaluation's auc: 0.830192 [4629] Train's auc: 0.990563 Evaluation's auc: 0.830188 [4630] Train's auc: 0.990563 Evaluation's auc: 0.830188 [4631] Train's auc: 0.990561 Evaluation's auc: 0.830191 [4632] Train's auc: 0.990563 Evaluation's auc: 0.830177 [4633] Train's auc: 0.990565 Evaluation's auc: 0.830178 [4634] Train's auc: 0.99057 Evaluation's auc: 0.830173 [4635] Train's auc: 0.990574 Evaluation's auc: 0.830189 [4636] Train's auc: 0.990581 Evaluation's auc: 0.830171 [4637] Train's auc: 0.990581 Evaluation's auc: 0.830171 [4638] Train's auc: 0.990587 Evaluation's auc: 0.830209 [4639] Train's auc: 0.990588 Evaluation's auc: 0.830201 [4640] Train's auc: 0.990591 Evaluation's auc: 0.830199 [4641] Train's auc: 0.990592 Evaluation's auc: 0.830203 [4642] Train's auc: 0.990596 Evaluation's auc: 0.830201 [4643] Train's auc: 0.9906 Evaluation's auc: 0.830201 [4644] Train's auc: 0.990602 Evaluation's auc: 0.830209 [4645] Train's auc: 0.990603 Evaluation's auc: 0.830207 [4646] Train's auc: 0.990604 Evaluation's auc: 0.830204 [4647] Train's auc: 0.990604 Evaluation's auc: 0.830203 [4648] Train's auc: 0.990604 Evaluation's auc: 0.830202 [4649] Train's auc: 0.990607 Evaluation's auc: 0.830216 [4650] Train's auc: 0.990609 Evaluation's auc: 0.830204 [4651] Train's auc: 0.990611 Evaluation's auc: 0.830195 [4652] Train's auc: 0.990612 Evaluation's auc: 0.830194 [4653] Train's auc: 0.990613 Evaluation's auc: 0.830182 [4654] Train's auc: 0.990614 Evaluation's auc: 0.830174 [4655] Train's auc: 0.990614 Evaluation's auc: 0.83018 [4656] Train's auc: 0.990614 Evaluation's auc: 0.83018 [4657] Train's auc: 0.990614 Evaluation's auc: 0.83018 [4658] Train's auc: 0.990614 Evaluation's auc: 0.83018 [4659] Train's auc: 0.990613 Evaluation's auc: 0.830179 [4660] Train's auc: 0.990614 Evaluation's auc: 0.830188 [4661] Train's auc: 0.990615 Evaluation's auc: 0.830196 [4662] Train's auc: 0.990633 Evaluation's auc: 0.830198 [4663] Train's auc: 0.990633 Evaluation's auc: 0.830199 [4664] Train's auc: 0.990633 Evaluation's auc: 0.830199 [4665] Train's auc: 0.990633 Evaluation's auc: 0.8302 [4666] Train's auc: 0.990634 Evaluation's auc: 0.830202 [4667] Train's auc: 0.990637 Evaluation's auc: 0.830169 [4668] Train's auc: 0.990636 Evaluation's auc: 0.830173 [4669] Train's auc: 0.990636 Evaluation's auc: 0.830173 [4670] Train's auc: 0.990636 Evaluation's auc: 0.830173 [4671] Train's auc: 0.990636 Evaluation's auc: 0.830171 [4672] Train's auc: 0.990636 Evaluation's auc: 0.830172 [4673] Train's auc: 0.990636 Evaluation's auc: 0.830172 [4674] Train's auc: 0.990636 Evaluation's auc: 0.830172 [4675] Train's auc: 0.990637 Evaluation's auc: 0.830164 [4676] Train's auc: 0.990641 Evaluation's auc: 0.830157 [4677] Train's auc: 0.990641 Evaluation's auc: 0.830157 [4678] Train's auc: 0.990643 Evaluation's auc: 0.830149 [4679] Train's auc: 0.990644 Evaluation's auc: 0.830146 [4680] Train's auc: 0.990645 Evaluation's auc: 0.830146 [4681] Train's auc: 0.990645 Evaluation's auc: 0.830145 [4682] Train's auc: 0.990645 Evaluation's auc: 0.830147 [4683] Train's auc: 0.990645 Evaluation's auc: 0.830147 [4684] Train's auc: 0.990645 Evaluation's auc: 0.830151 [4685] Train's auc: 0.990645 Evaluation's auc: 0.830151 [4686] Train's auc: 0.990645 Evaluation's auc: 0.830151 [4687] Train's auc: 0.990644 Evaluation's auc: 0.830154 [4688] Train's auc: 0.990642 Evaluation's auc: 0.830137 [4689] Train's auc: 0.990641 Evaluation's auc: 0.830137 [4690] Train's auc: 0.990641 Evaluation's auc: 0.830137 [4691] Train's auc: 0.99064 Evaluation's auc: 0.83014 [4692] Train's auc: 0.99064 Evaluation's auc: 0.83014 [4693] Train's auc: 0.990641 Evaluation's auc: 0.830134 [4694] Train's auc: 0.990641 Evaluation's auc: 0.830134 [4695] Train's auc: 0.990641 Evaluation's auc: 0.830134 [4696] Train's auc: 0.990641 Evaluation's auc: 0.830134 [4697] Train's auc: 0.990641 Evaluation's auc: 0.830134 [4698] Train's auc: 0.990641 Evaluation's auc: 0.830134 [4699] Train's auc: 0.990641 Evaluation's auc: 0.830135 [4700] Train's auc: 0.990641 Evaluation's auc: 0.830135 [4701] Train's auc: 0.990641 Evaluation's auc: 0.830135 [4702] Train's auc: 0.990641 Evaluation's auc: 0.830134 [4703] Train's auc: 0.990642 Evaluation's auc: 0.830133 [4704] Train's auc: 0.990643 Evaluation's auc: 0.83013 [4705] Train's auc: 0.990643 Evaluation's auc: 0.830124 [4706] Train's auc: 0.990643 Evaluation's auc: 0.830125 [4707] Train's auc: 0.990643 Evaluation's auc: 0.830125 [4708] Train's auc: 0.990643 Evaluation's auc: 0.830125 [4709] Train's auc: 0.990643 Evaluation's auc: 0.830124 [4710] Train's auc: 0.990643 Evaluation's auc: 0.830124 [4711] Train's auc: 0.990643 Evaluation's auc: 0.830125 [4712] Train's auc: 0.990643 Evaluation's auc: 0.830126 [4713] Train's auc: 0.990642 Evaluation's auc: 0.830127 [4714] Train's auc: 0.990642 Evaluation's auc: 0.830127 [4715] Train's auc: 0.990642 Evaluation's auc: 0.830138 [4716] Train's auc: 0.990643 Evaluation's auc: 0.830137 [4717] Train's auc: 0.990643 Evaluation's auc: 0.83014 [4718] Train's auc: 0.990643 Evaluation's auc: 0.830141 [4719] Train's auc: 0.990643 Evaluation's auc: 0.830141 [4720] Train's auc: 0.990645 Evaluation's auc: 0.830132 [4721] Train's auc: 0.990647 Evaluation's auc: 0.830146 [4722] Train's auc: 0.990649 Evaluation's auc: 0.830127 [4723] Train's auc: 0.990649 Evaluation's auc: 0.830127 [4724] Train's auc: 0.990649 Evaluation's auc: 0.830127 [4725] Train's auc: 0.990648 Evaluation's auc: 0.830129 [4726] Train's auc: 0.990648 Evaluation's auc: 0.830129 [4727] Train's auc: 0.990648 Evaluation's auc: 0.830131 [4728] Train's auc: 0.990648 Evaluation's auc: 0.830114 [4729] Train's auc: 0.990648 Evaluation's auc: 0.830114 [4730] Train's auc: 0.990648 Evaluation's auc: 0.830114 [4731] Train's auc: 0.990648 Evaluation's auc: 0.830114 [4732] Train's auc: 0.990648 Evaluation's auc: 0.830114 [4733] Train's auc: 0.990649 Evaluation's auc: 0.830113 [4734] Train's auc: 0.990649 Evaluation's auc: 0.830113 [4735] Train's auc: 0.990648 Evaluation's auc: 0.830115 [4736] Train's auc: 0.990653 Evaluation's auc: 0.830091 [4737] Train's auc: 0.990653 Evaluation's auc: 0.830095 [4738] Train's auc: 0.990658 Evaluation's auc: 0.830087 [4739] Train's auc: 0.990658 Evaluation's auc: 0.830087 [4740] Train's auc: 0.990658 Evaluation's auc: 0.830087 [4741] Train's auc: 0.990658 Evaluation's auc: 0.830087 [4742] Train's auc: 0.990658 Evaluation's auc: 0.830087 [4743] Train's auc: 0.990658 Evaluation's auc: 0.830087 [4744] Train's auc: 0.990658 Evaluation's auc: 0.830087 [4745] Train's auc: 0.990658 Evaluation's auc: 0.830087 [4746] Train's auc: 0.990658 Evaluation's auc: 0.830087 [4747] Train's auc: 0.990659 Evaluation's auc: 0.830086 [4748] Train's auc: 0.990659 Evaluation's auc: 0.830086 [4749] Train's auc: 0.990659 Evaluation's auc: 0.830086 [4750] Train's auc: 0.990659 Evaluation's auc: 0.830086 [4751] Train's auc: 0.990659 Evaluation's auc: 0.830085 [4752] Train's auc: 0.990659 Evaluation's auc: 0.830085 [4753] Train's auc: 0.990659 Evaluation's auc: 0.830085 [4754] Train's auc: 0.99066 Evaluation's auc: 0.830082 [4755] Train's auc: 0.990664 Evaluation's auc: 0.830083 [4756] Train's auc: 0.990664 Evaluation's auc: 0.830078 [4757] Train's auc: 0.990664 Evaluation's auc: 0.830076 [4758] Train's auc: 0.990664 Evaluation's auc: 0.830077 [4759] Train's auc: 0.990664 Evaluation's auc: 0.830077 [4760] Train's auc: 0.990664 Evaluation's auc: 0.830079 [4761] Train's auc: 0.990664 Evaluation's auc: 0.830079 [4762] Train's auc: 0.990664 Evaluation's auc: 0.83008 [4763] Train's auc: 0.990664 Evaluation's auc: 0.83008 [4764] Train's auc: 0.990664 Evaluation's auc: 0.830081 [4765] Train's auc: 0.990664 Evaluation's auc: 0.830082 [4766] Train's auc: 0.990664 Evaluation's auc: 0.830082 [4767] Train's auc: 0.990664 Evaluation's auc: 0.830082 [4768] Train's auc: 0.990664 Evaluation's auc: 0.830082 [4769] Train's auc: 0.990664 Evaluation's auc: 0.830082 [4770] Train's auc: 0.990664 Evaluation's auc: 0.830082 [4771] Train's auc: 0.990663 Evaluation's auc: 0.830097 [4772] Train's auc: 0.990663 Evaluation's auc: 0.830097 [4773] Train's auc: 0.990663 Evaluation's auc: 0.830097 [4774] Train's auc: 0.990661 Evaluation's auc: 0.830097 [4775] Train's auc: 0.990663 Evaluation's auc: 0.830091 [4776] Train's auc: 0.990663 Evaluation's auc: 0.8301 [4777] Train's auc: 0.990663 Evaluation's auc: 0.830101 [4778] Train's auc: 0.990663 Evaluation's auc: 0.830101 [4779] Train's auc: 0.990664 Evaluation's auc: 0.830101 [4780] Train's auc: 0.990663 Evaluation's auc: 0.830112 [4781] Train's auc: 0.990665 Evaluation's auc: 0.830111 [4782] Train's auc: 0.990666 Evaluation's auc: 0.830112 [4783] Train's auc: 0.990667 Evaluation's auc: 0.830109 [4784] Train's auc: 0.990669 Evaluation's auc: 0.830109 [4785] Train's auc: 0.990669 Evaluation's auc: 0.830106 [4786] Train's auc: 0.99067 Evaluation's auc: 0.830104 [4787] Train's auc: 0.990676 Evaluation's auc: 0.830105 [4788] Train's auc: 0.990677 Evaluation's auc: 0.830107 [4789] Train's auc: 0.990677 Evaluation's auc: 0.830107 [4790] Train's auc: 0.990677 Evaluation's auc: 0.830107 [4791] Train's auc: 0.99068 Evaluation's auc: 0.830102 [4792] Train's auc: 0.990679 Evaluation's auc: 0.830101 [4793] Train's auc: 0.990683 Evaluation's auc: 0.830092 [4794] Train's auc: 0.990683 Evaluation's auc: 0.830092 [4795] Train's auc: 0.990682 Evaluation's auc: 0.830109 [4796] Train's auc: 0.990684 Evaluation's auc: 0.830111 [4797] Train's auc: 0.990684 Evaluation's auc: 0.830102 [4798] Train's auc: 0.990683 Evaluation's auc: 0.830099 [4799] Train's auc: 0.990684 Evaluation's auc: 0.830101 [4800] Train's auc: 0.990684 Evaluation's auc: 0.830101 [4801] Train's auc: 0.990684 Evaluation's auc: 0.830105 [4802] Train's auc: 0.990683 Evaluation's auc: 0.830105 [4803] Train's auc: 0.990684 Evaluation's auc: 0.830104 [4804] Train's auc: 0.990684 Evaluation's auc: 0.830104 [4805] Train's auc: 0.990684 Evaluation's auc: 0.830103 [4806] Train's auc: 0.990685 Evaluation's auc: 0.830102 [4807] Train's auc: 0.990684 Evaluation's auc: 0.830102 [4808] Train's auc: 0.990686 Evaluation's auc: 0.830084 [4809] Train's auc: 0.990687 Evaluation's auc: 0.830084 [4810] Train's auc: 0.990687 Evaluation's auc: 0.830084 [4811] Train's auc: 0.990687 Evaluation's auc: 0.830084 [4812] Train's auc: 0.990687 Evaluation's auc: 0.830084 [4813] Train's auc: 0.990686 Evaluation's auc: 0.830103 [4814] Train's auc: 0.990687 Evaluation's auc: 0.830081 [4815] Train's auc: 0.990687 Evaluation's auc: 0.830081 [4816] Train's auc: 0.990687 Evaluation's auc: 0.830081 [4817] Train's auc: 0.990687 Evaluation's auc: 0.830081 [4818] Train's auc: 0.990687 Evaluation's auc: 0.830081 [4819] Train's auc: 0.990687 Evaluation's auc: 0.830081 [4820] Train's auc: 0.990687 Evaluation's auc: 0.830082 [4821] Train's auc: 0.990687 Evaluation's auc: 0.830083 [4822] Train's auc: 0.990687 Evaluation's auc: 0.830083 [4823] Train's auc: 0.990687 Evaluation's auc: 0.830083 [4824] Train's auc: 0.990687 Evaluation's auc: 0.830083 [4825] Train's auc: 0.990687 Evaluation's auc: 0.830083 [4826] Train's auc: 0.990687 Evaluation's auc: 0.830083 [4827] Train's auc: 0.990687 Evaluation's auc: 0.830083 [4828] Train's auc: 0.990687 Evaluation's auc: 0.830083 [4829] Train's auc: 0.990687 Evaluation's auc: 0.830083 [4830] Train's auc: 0.990687 Evaluation's auc: 0.830083 [4831] Train's auc: 0.990687 Evaluation's auc: 0.83008 [4832] Train's auc: 0.990687 Evaluation's auc: 0.83008 [4833] Train's auc: 0.990687 Evaluation's auc: 0.83008 [4834] Train's auc: 0.990687 Evaluation's auc: 0.83008 [4835] Train's auc: 0.990687 Evaluation's auc: 0.83008 [4836] Train's auc: 0.990687 Evaluation's auc: 0.83008 [4837] Train's auc: 0.990687 Evaluation's auc: 0.830095 [4838] Train's auc: 0.990688 Evaluation's auc: 0.830096 [4839] Train's auc: 0.990688 Evaluation's auc: 0.830095 [4840] Train's auc: 0.99069 Evaluation's auc: 0.830098 [4841] Train's auc: 0.99069 Evaluation's auc: 0.830097 [4842] Train's auc: 0.990689 Evaluation's auc: 0.830097 [4843] Train's auc: 0.990689 Evaluation's auc: 0.830092 [4844] Train's auc: 0.990689 Evaluation's auc: 0.830087 [4845] Train's auc: 0.990689 Evaluation's auc: 0.830087 [4846] Train's auc: 0.990689 Evaluation's auc: 0.830087 [4847] Train's auc: 0.990689 Evaluation's auc: 0.830087 [4848] Train's auc: 0.990688 Evaluation's auc: 0.830096 [4849] Train's auc: 0.990689 Evaluation's auc: 0.830095 [4850] Train's auc: 0.990688 Evaluation's auc: 0.830097 [4851] Train's auc: 0.990689 Evaluation's auc: 0.830096 [4852] Train's auc: 0.990689 Evaluation's auc: 0.830096 [4853] Train's auc: 0.990689 Evaluation's auc: 0.830095 [4854] Train's auc: 0.990688 Evaluation's auc: 0.83011 [4855] Train's auc: 0.990688 Evaluation's auc: 0.83011 [4856] Train's auc: 0.99069 Evaluation's auc: 0.830104 [4857] Train's auc: 0.990689 Evaluation's auc: 0.830104 [4858] Train's auc: 0.990691 Evaluation's auc: 0.830097 [4859] Train's auc: 0.990691 Evaluation's auc: 0.830087 [4860] Train's auc: 0.990691 Evaluation's auc: 0.830087 [4861] Train's auc: 0.990691 Evaluation's auc: 0.830086 [4862] Train's auc: 0.990691 Evaluation's auc: 0.830086 [4863] Train's auc: 0.990691 Evaluation's auc: 0.830086 [4864] Train's auc: 0.990691 Evaluation's auc: 0.830085 [4865] Train's auc: 0.990691 Evaluation's auc: 0.830085 [4866] Train's auc: 0.990691 Evaluation's auc: 0.830085 [4867] Train's auc: 0.990691 Evaluation's auc: 0.830085 [4868] Train's auc: 0.990691 Evaluation's auc: 0.830085 [4869] Train's auc: 0.990691 Evaluation's auc: 0.830085 [4870] Train's auc: 0.990691 Evaluation's auc: 0.830085 [4871] Train's auc: 0.990692 Evaluation's auc: 0.830098 [4872] Train's auc: 0.990692 Evaluation's auc: 0.830098 [4873] Train's auc: 0.990692 Evaluation's auc: 0.830098 [4874] Train's auc: 0.990692 Evaluation's auc: 0.830098 [4875] Train's auc: 0.990692 Evaluation's auc: 0.830098 [4876] Train's auc: 0.990692 Evaluation's auc: 0.830098 [4877] Train's auc: 0.990692 Evaluation's auc: 0.830098 [4878] Train's auc: 0.990692 Evaluation's auc: 0.830098 [4879] Train's auc: 0.990692 Evaluation's auc: 0.830098 [4880] Train's auc: 0.990692 Evaluation's auc: 0.830098 [4881] Train's auc: 0.990692 Evaluation's auc: 0.830095 [4882] Train's auc: 0.990692 Evaluation's auc: 0.830095 [4883] Train's auc: 0.990692 Evaluation's auc: 0.830095 [4884] Train's auc: 0.990692 Evaluation's auc: 0.830095 [4885] Train's auc: 0.990692 Evaluation's auc: 0.830095 [4886] Train's auc: 0.990692 Evaluation's auc: 0.830095 [4887] Train's auc: 0.990692 Evaluation's auc: 0.830095 [4888] Train's auc: 0.990692 Evaluation's auc: 0.830095 [4889] Train's auc: 0.990692 Evaluation's auc: 0.830095 [4890] Train's auc: 0.990692 Evaluation's auc: 0.830095 [4891] Train's auc: 0.990692 Evaluation's auc: 0.830095 [4892] Train's auc: 0.990692 Evaluation's auc: 0.830095 [4893] Train's auc: 0.990692 Evaluation's auc: 0.830095 [4894] Train's auc: 0.990692 Evaluation's auc: 0.830095 [4895] Train's auc: 0.990692 Evaluation's auc: 0.830095 [4896] Train's auc: 0.990693 Evaluation's auc: 0.830105 [4897] Train's auc: 0.990692 Evaluation's auc: 0.830106 [4898] Train's auc: 0.990693 Evaluation's auc: 0.830107 [4899] Train's auc: 0.990693 Evaluation's auc: 0.830107 [4900] Train's auc: 0.990693 Evaluation's auc: 0.830107 [4901] Train's auc: 0.990693 Evaluation's auc: 0.830107 [4902] Train's auc: 0.990693 Evaluation's auc: 0.830104 [4903] Train's auc: 0.990693 Evaluation's auc: 0.830103 [4904] Train's auc: 0.990693 Evaluation's auc: 0.830104 [4905] Train's auc: 0.990693 Evaluation's auc: 0.830104 [4906] Train's auc: 0.990693 Evaluation's auc: 0.830104 [4907] Train's auc: 0.990693 Evaluation's auc: 0.830104 [4908] Train's auc: 0.990693 Evaluation's auc: 0.830106 [4909] Train's auc: 0.990693 Evaluation's auc: 0.830106 [4910] Train's auc: 0.990693 Evaluation's auc: 0.830106 [4911] Train's auc: 0.990693 Evaluation's auc: 0.830106 [4912] Train's auc: 0.990693 Evaluation's auc: 0.830106 [4913] Train's auc: 0.990693 Evaluation's auc: 0.830106 [4914] Train's auc: 0.990693 Evaluation's auc: 0.830106 [4915] Train's auc: 0.990693 Evaluation's auc: 0.830106 [4916] Train's auc: 0.990693 Evaluation's auc: 0.830106 [4917] Train's auc: 0.990693 Evaluation's auc: 0.830106 [4918] Train's auc: 0.990694 Evaluation's auc: 0.830105 [4919] Train's auc: 0.990694 Evaluation's auc: 0.830105 [4920] Train's auc: 0.990692 Evaluation's auc: 0.830113 [4921] Train's auc: 0.990694 Evaluation's auc: 0.830118 [4922] Train's auc: 0.990695 Evaluation's auc: 0.830109 [4923] Train's auc: 0.990696 Evaluation's auc: 0.830114 [4924] Train's auc: 0.990696 Evaluation's auc: 0.830107 [4925] Train's auc: 0.990696 Evaluation's auc: 0.830107 [4926] Train's auc: 0.990696 Evaluation's auc: 0.830107 [4927] Train's auc: 0.990696 Evaluation's auc: 0.830108 [4928] Train's auc: 0.990696 Evaluation's auc: 0.830108 [4929] Train's auc: 0.990696 Evaluation's auc: 0.830108 [4930] Train's auc: 0.990696 Evaluation's auc: 0.830108 [4931] Train's auc: 0.990695 Evaluation's auc: 0.830109 [4932] Train's auc: 0.990695 Evaluation's auc: 0.830111 [4933] Train's auc: 0.990695 Evaluation's auc: 0.830111 [4934] Train's auc: 0.990695 Evaluation's auc: 0.830111 [4935] Train's auc: 0.990695 Evaluation's auc: 0.830111 [4936] Train's auc: 0.990695 Evaluation's auc: 0.830113 [4937] Train's auc: 0.990695 Evaluation's auc: 0.830113 [4938] Train's auc: 0.990695 Evaluation's auc: 0.830112 [4939] Train's auc: 0.990695 Evaluation's auc: 0.830112 [4940] Train's auc: 0.990695 Evaluation's auc: 0.830112 [4941] Train's auc: 0.990695 Evaluation's auc: 0.830112 [4942] Train's auc: 0.990693 Evaluation's auc: 0.830112 [4943] Train's auc: 0.990694 Evaluation's auc: 0.830112 [4944] Train's auc: 0.990697 Evaluation's auc: 0.830113 [4945] Train's auc: 0.990698 Evaluation's auc: 0.830112 [4946] Train's auc: 0.990703 Evaluation's auc: 0.830111 [4947] Train's auc: 0.990702 Evaluation's auc: 0.830115 [4948] Train's auc: 0.990705 Evaluation's auc: 0.830103 [4949] Train's auc: 0.990705 Evaluation's auc: 0.830101 [4950] Train's auc: 0.990706 Evaluation's auc: 0.830096 [4951] Train's auc: 0.990708 Evaluation's auc: 0.830098 [4952] Train's auc: 0.99071 Evaluation's auc: 0.830063 [4953] Train's auc: 0.990711 Evaluation's auc: 0.830064 [4954] Train's auc: 0.990711 Evaluation's auc: 0.830065 [4955] Train's auc: 0.990712 Evaluation's auc: 0.830061 [4956] Train's auc: 0.990712 Evaluation's auc: 0.830064 [4957] Train's auc: 0.990714 Evaluation's auc: 0.830061 [4958] Train's auc: 0.99072 Evaluation's auc: 0.830059 [4959] Train's auc: 0.990722 Evaluation's auc: 0.830047 [4960] Train's auc: 0.990722 Evaluation's auc: 0.830047 [4961] Train's auc: 0.990723 Evaluation's auc: 0.830047 [4962] Train's auc: 0.990723 Evaluation's auc: 0.830047 [4963] Train's auc: 0.990723 Evaluation's auc: 0.830047 [4964] Train's auc: 0.990723 Evaluation's auc: 0.830047 [4965] Train's auc: 0.990722 Evaluation's auc: 0.830048 [4966] Train's auc: 0.990729 Evaluation's auc: 0.830121 [4967] Train's auc: 0.990729 Evaluation's auc: 0.83012 [4968] Train's auc: 0.99073 Evaluation's auc: 0.830119 [4969] Train's auc: 0.99073 Evaluation's auc: 0.830119 [4970] Train's auc: 0.990729 Evaluation's auc: 0.830121 [4971] Train's auc: 0.990732 Evaluation's auc: 0.830131 [4972] Train's auc: 0.990733 Evaluation's auc: 0.830116 [4973] Train's auc: 0.990733 Evaluation's auc: 0.830116 [4974] Train's auc: 0.990733 Evaluation's auc: 0.830115 [4975] Train's auc: 0.990733 Evaluation's auc: 0.830114 [4976] Train's auc: 0.990733 Evaluation's auc: 0.830122 [4977] Train's auc: 0.990735 Evaluation's auc: 0.830122 [4978] Train's auc: 0.990738 Evaluation's auc: 0.830137 [4979] Train's auc: 0.990744 Evaluation's auc: 0.830124 [4980] Train's auc: 0.990742 Evaluation's auc: 0.830137 [4981] Train's auc: 0.990743 Evaluation's auc: 0.830123 [4982] Train's auc: 0.990748 Evaluation's auc: 0.830118 [4983] Train's auc: 0.990753 Evaluation's auc: 0.830108 [4984] Train's auc: 0.990756 Evaluation's auc: 0.83011 [4985] Train's auc: 0.990755 Evaluation's auc: 0.830112 [4986] Train's auc: 0.990755 Evaluation's auc: 0.830113 [4987] Train's auc: 0.990755 Evaluation's auc: 0.830112 [4988] Train's auc: 0.990756 Evaluation's auc: 0.830095 [4989] Train's auc: 0.990757 Evaluation's auc: 0.830089 [4990] Train's auc: 0.990756 Evaluation's auc: 0.83007 [4991] Train's auc: 0.990756 Evaluation's auc: 0.830068 [4992] Train's auc: 0.990756 Evaluation's auc: 0.830068 [4993] Train's auc: 0.990756 Evaluation's auc: 0.830068 [4994] Train's auc: 0.990755 Evaluation's auc: 0.830071 [4995] Train's auc: 0.990755 Evaluation's auc: 0.83007 [4996] Train's auc: 0.990755 Evaluation's auc: 0.83007 [4997] Train's auc: 0.990755 Evaluation's auc: 0.830072 [4998] Train's auc: 0.990755 Evaluation's auc: 0.830071 [4999] Train's auc: 0.990756 Evaluation's auc: 0.830068 [5000] Train's auc: 0.990758 Evaluation's auc: 0.830068
from sklearn.model_selection import GridSearchCV
lgb_grid_params = {
'boosting_type':['dart','gbdt'],
'learning_rate': [0.005, 0.01, 0.0001],
'n_estimators' : [3, 5],
'num_leaves': [12,16,20],
'random_state' : [501]
# Updated from 'seed'
#'colsample_bytree' : [???],
#'subsample' : [???],
#'reg_alpha' : [???],
#'reg_lambda' : [???],
}
# We can include early stopping with gradient boosted decisino trees:
fit_params={"early_stopping_rounds":10,
"eval_set" : [[x_val, y_val]]}
lgb_mdl_gs = lgb.LGBMClassifier(boosting_type = 'gbdt',
n_jobs = -1,
objective = 'binary',
num_iterations = 100,
metric = 'auc'
)
lgb_grid_mdl = GridSearchCV(lgb_mdl_gs, lgb_grid_params,
verbose=0,
cv=4)
lgb_grid_mdl
GridSearchCV(cv=4, error_score=nan,
estimator=LGBMClassifier(boosting_type='gbdt', class_weight=None,
colsample_bytree=1.0,
importance_type='split',
learning_rate=0.1, max_depth=-1,
metric='auc', min_child_samples=20,
min_child_weight=0.001,
min_split_gain=0.0, n_estimators=100,
n_jobs=-1, num_iterations=100,
num_leaves=31, objective='binary',
random_state=None, reg...ha=0.0,
reg_lambda=0.0, silent=True,
subsample=1.0, subsample_for_bin=200000,
subsample_freq=0),
iid='deprecated', n_jobs=None,
param_grid={'boosting_type': ['dart', 'gbdt'],
'learning_rate': [0.005, 0.01, 0.0001],
'n_estimators': [3, 5], 'num_leaves': [12, 16, 20],
'random_state': [501]},
pre_dispatch='2*n_jobs', refit=True, return_train_score=False,
scoring=None, verbose=0)
lgb_grid_mdl.get_params().keys()
dict_keys(['cv', 'error_score', 'estimator__boosting_type', 'estimator__class_weight', 'estimator__colsample_bytree', 'estimator__importance_type', 'estimator__learning_rate', 'estimator__max_depth', 'estimator__min_child_samples', 'estimator__min_child_weight', 'estimator__min_split_gain', 'estimator__n_estimators', 'estimator__n_jobs', 'estimator__num_leaves', 'estimator__objective', 'estimator__random_state', 'estimator__reg_alpha', 'estimator__reg_lambda', 'estimator__silent', 'estimator__subsample', 'estimator__subsample_for_bin', 'estimator__subsample_freq', 'estimator__num_iterations', 'estimator__metric', 'estimator', 'iid', 'n_jobs', 'param_grid', 'pre_dispatch', 'refit', 'return_train_score', 'scoring', 'verbose'])
lgb_grid_mdl.fit(x_train, y_train, **fit_params)
/Users/piumallick/anaconda3/lib/python3.7/site-packages/lightgbm/engine.py:148: UserWarning: Found `num_iterations` in params. Will use it instead of argument
warnings.warn("Found `{}` in params. Will use it instead of argument".format(alias))
[1] valid_0's auc: 0.7495 [2] valid_0's auc: 0.7495 [3] valid_0's auc: 0.7495 [4] valid_0's auc: 0.7495 [5] valid_0's auc: 0.7495 [6] valid_0's auc: 0.7495 [7] valid_0's auc: 0.7495 [8] valid_0's auc: 0.751338 [9] valid_0's auc: 0.751338 [10] valid_0's auc: 0.751078 [11] valid_0's auc: 0.751078 [12] valid_0's auc: 0.751338 [13] valid_0's auc: 0.751338
/Users/piumallick/anaconda3/lib/python3.7/site-packages/lightgbm/callback.py:192: UserWarning: Early stopping is not available in dart mode
warnings.warn('Early stopping is not available in dart mode')
[14] valid_0's auc: 0.751338 [15] valid_0's auc: 0.751078 [16] valid_0's auc: 0.751078 [17] valid_0's auc: 0.749299 [18] valid_0's auc: 0.749299 [19] valid_0's auc: 0.749299 [20] valid_0's auc: 0.749299 [21] valid_0's auc: 0.749299 [22] valid_0's auc: 0.751078 [23] valid_0's auc: 0.751078 [24] valid_0's auc: 0.753588 [25] valid_0's auc: 0.753588 [26] valid_0's auc: 0.753588 [27] valid_0's auc: 0.752608 [28] valid_0's auc: 0.752634 [29] valid_0's auc: 0.752634 [30] valid_0's auc: 0.752634 [31] valid_0's auc: 0.753588 [32] valid_0's auc: 0.753588 [33] valid_0's auc: 0.752608 [34] valid_0's auc: 0.752608 [35] valid_0's auc: 0.752634 [36] valid_0's auc: 0.753663 [37] valid_0's auc: 0.753588 [38] valid_0's auc: 0.753817 [39] valid_0's auc: 0.753817 [40] valid_0's auc: 0.753801 [41] valid_0's auc: 0.753622 [42] valid_0's auc: 0.754569 [43] valid_0's auc: 0.754617 [44] valid_0's auc: 0.754617 [45] valid_0's auc: 0.754608 [46] valid_0's auc: 0.754558 [47] valid_0's auc: 0.754558 [48] valid_0's auc: 0.754558 [49] valid_0's auc: 0.754628 [50] valid_0's auc: 0.754558 [51] valid_0's auc: 0.754579 [52] valid_0's auc: 0.754617 [53] valid_0's auc: 0.754621 [54] valid_0's auc: 0.75465 [55] valid_0's auc: 0.756121 [56] valid_0's auc: 0.75612 [57] valid_0's auc: 0.756265 [58] valid_0's auc: 0.756265 [59] valid_0's auc: 0.756265 [60] valid_0's auc: 0.756283 [61] valid_0's auc: 0.756283 [62] valid_0's auc: 0.756245 [63] valid_0's auc: 0.756262 [64] valid_0's auc: 0.756262 [65] valid_0's auc: 0.756285 [66] valid_0's auc: 0.756247 [67] valid_0's auc: 0.756247 [68] valid_0's auc: 0.756285 [69] valid_0's auc: 0.756247 [70] valid_0's auc: 0.756247 [71] valid_0's auc: 0.756247 [72] valid_0's auc: 0.756247 [73] valid_0's auc: 0.756247 [74] valid_0's auc: 0.756247 [75] valid_0's auc: 0.756247 [76] valid_0's auc: 0.756246 [77] valid_0's auc: 0.7563 [78] valid_0's auc: 0.756268 [79] valid_0's auc: 0.756322 [80] valid_0's auc: 0.756322 [81] valid_0's auc: 0.762092 [82] valid_0's auc: 0.762097 [83] valid_0's auc: 0.762082 [84] valid_0's auc: 0.762117 [85] valid_0's auc: 0.762138 [86] valid_0's auc: 0.762142 [87] valid_0's auc: 0.762142 [88] valid_0's auc: 0.762142 [89] valid_0's auc: 0.762133 [90] valid_0's auc: 0.762127 [91] valid_0's auc: 0.762118 [92] valid_0's auc: 0.762166 [93] valid_0's auc: 0.762127 [94] valid_0's auc: 0.762127 [95] valid_0's auc: 0.762173 [96] valid_0's auc: 0.762131 [97] valid_0's auc: 0.762127 [98] valid_0's auc: 0.762461 [99] valid_0's auc: 0.762457 [100] valid_0's auc: 0.762457 [1] valid_0's auc: 0.748453 [2] valid_0's auc: 0.749691 [3] valid_0's auc: 0.751615 [4] valid_0's auc: 0.751094 [5] valid_0's auc: 0.751119 [6] valid_0's auc: 0.752006 [7] valid_0's auc: 0.752006 [8] valid_0's auc: 0.751982 [9] valid_0's auc: 0.752532 [10] valid_0's auc: 0.756575 [11] valid_0's auc: 0.756658 [12] valid_0's auc: 0.756658 [13] valid_0's auc: 0.756638 [14] valid_0's auc: 0.756577 [15] valid_0's auc: 0.756643 [16] valid_0's auc: 0.756819 [17] valid_0's auc: 0.756629 [18] valid_0's auc: 0.756785 [19] valid_0's auc: 0.756519 [20] valid_0's auc: 0.756519 [21] valid_0's auc: 0.756542 [22] valid_0's auc: 0.756415 [23] valid_0's auc: 0.756415 [24] valid_0's auc: 0.756995 [25] valid_0's auc: 0.757296 [26] valid_0's auc: 0.757296 [27] valid_0's auc: 0.756938 [28] valid_0's auc: 0.756638 [29] valid_0's auc: 0.756657 [30] valid_0's auc: 0.756656 [31] valid_0's auc: 0.756939 [32] valid_0's auc: 0.756922 [33] valid_0's auc: 0.756658 [34] valid_0's auc: 0.756658 [35] valid_0's auc: 0.75676 [36] valid_0's auc: 0.756836 [37] valid_0's auc: 0.758193 [38] valid_0's auc: 0.761837 [39] valid_0's auc: 0.761771 [40] valid_0's auc: 0.76182 [41] valid_0's auc: 0.761735 [42] valid_0's auc: 0.762922 [43] valid_0's auc: 0.76256 [44] valid_0's auc: 0.762561 [45] valid_0's auc: 0.762974 [46] valid_0's auc: 0.763946 [47] valid_0's auc: 0.763934 [48] valid_0's auc: 0.765772 [49] valid_0's auc: 0.766153 [50] valid_0's auc: 0.765867 [51] valid_0's auc: 0.766182 [52] valid_0's auc: 0.766029 [53] valid_0's auc: 0.766586 [54] valid_0's auc: 0.766755 [55] valid_0's auc: 0.766879 [56] valid_0's auc: 0.766713 [57] valid_0's auc: 0.76723 [58] valid_0's auc: 0.767224 [59] valid_0's auc: 0.767274 [60] valid_0's auc: 0.76708 [61] valid_0's auc: 0.767084 [62] valid_0's auc: 0.767316 [63] valid_0's auc: 0.768125 [64] valid_0's auc: 0.768149 [65] valid_0's auc: 0.768159 [66] valid_0's auc: 0.768155 [67] valid_0's auc: 0.767995 [68] valid_0's auc: 0.767966 [69] valid_0's auc: 0.768898 [70] valid_0's auc: 0.768752 [71] valid_0's auc: 0.768493 [72] valid_0's auc: 0.768935 [73] valid_0's auc: 0.768953 [74] valid_0's auc: 0.76896 [75] valid_0's auc: 0.768928 [76] valid_0's auc: 0.769088 [77] valid_0's auc: 0.769044 [78] valid_0's auc: 0.769472 [79] valid_0's auc: 0.769704 [80] valid_0's auc: 0.770133 [81] valid_0's auc: 0.770279 [82] valid_0's auc: 0.77036 [83] valid_0's auc: 0.770189 [84] valid_0's auc: 0.770399 [85] valid_0's auc: 0.770458 [86] valid_0's auc: 0.770468 [87] valid_0's auc: 0.770465 [88] valid_0's auc: 0.770445 [89] valid_0's auc: 0.770423 [90] valid_0's auc: 0.770407 [91] valid_0's auc: 0.770374 [92] valid_0's auc: 0.770488 [93] valid_0's auc: 0.770414 [94] valid_0's auc: 0.770352 [95] valid_0's auc: 0.770421 [96] valid_0's auc: 0.770474 [97] valid_0's auc: 0.770517 [98] valid_0's auc: 0.770554 [99] valid_0's auc: 0.770537 [100] valid_0's auc: 0.770578 [1] valid_0's auc: 0.748867 [2] valid_0's auc: 0.762521 [3] valid_0's auc: 0.764062 [4] valid_0's auc: 0.763258 [5] valid_0's auc: 0.763258 [6] valid_0's auc: 0.762373 [7] valid_0's auc: 0.762373 [8] valid_0's auc: 0.762343 [9] valid_0's auc: 0.764046 [10] valid_0's auc: 0.763356 [11] valid_0's auc: 0.763356 [12] valid_0's auc: 0.763956 [13] valid_0's auc: 0.764331 [14] valid_0's auc: 0.763847 [15] valid_0's auc: 0.763082 [16] valid_0's auc: 0.762994 [17] valid_0's auc: 0.763904 [18] valid_0's auc: 0.764023 [19] valid_0's auc: 0.764023 [20] valid_0's auc: 0.764023 [21] valid_0's auc: 0.763919 [22] valid_0's auc: 0.76395 [23] valid_0's auc: 0.763922 [24] valid_0's auc: 0.76392 [25] valid_0's auc: 0.763752 [26] valid_0's auc: 0.764454 [27] valid_0's auc: 0.76508 [28] valid_0's auc: 0.764877 [29] valid_0's auc: 0.764979 [30] valid_0's auc: 0.764998 [31] valid_0's auc: 0.764434 [32] valid_0's auc: 0.764837 [33] valid_0's auc: 0.765323 [34] valid_0's auc: 0.76526 [35] valid_0's auc: 0.765255 [36] valid_0's auc: 0.765941 [37] valid_0's auc: 0.765249 [38] valid_0's auc: 0.766137 [39] valid_0's auc: 0.766162 [40] valid_0's auc: 0.765359 [41] valid_0's auc: 0.76535 [42] valid_0's auc: 0.765736 [43] valid_0's auc: 0.766502 [44] valid_0's auc: 0.766498 [45] valid_0's auc: 0.76613 [46] valid_0's auc: 0.766363 [47] valid_0's auc: 0.766347 [48] valid_0's auc: 0.766244 [49] valid_0's auc: 0.766738 [50] valid_0's auc: 0.766597 [51] valid_0's auc: 0.767732 [52] valid_0's auc: 0.767454 [53] valid_0's auc: 0.767521 [54] valid_0's auc: 0.767431 [55] valid_0's auc: 0.767401 [56] valid_0's auc: 0.768159 [57] valid_0's auc: 0.767965 [58] valid_0's auc: 0.768016 [59] valid_0's auc: 0.767889 [60] valid_0's auc: 0.767804 [61] valid_0's auc: 0.767866 [62] valid_0's auc: 0.768152 [63] valid_0's auc: 0.767838 [64] valid_0's auc: 0.767946 [65] valid_0's auc: 0.767746 [66] valid_0's auc: 0.767741 [67] valid_0's auc: 0.767787 [68] valid_0's auc: 0.767848 [69] valid_0's auc: 0.767646 [70] valid_0's auc: 0.768215 [71] valid_0's auc: 0.768195 [72] valid_0's auc: 0.768186 [73] valid_0's auc: 0.768187 [74] valid_0's auc: 0.768195 [75] valid_0's auc: 0.768135 [76] valid_0's auc: 0.768456 [77] valid_0's auc: 0.768422 [78] valid_0's auc: 0.768505 [79] valid_0's auc: 0.768409 [80] valid_0's auc: 0.768388 [81] valid_0's auc: 0.768728 [82] valid_0's auc: 0.768667 [83] valid_0's auc: 0.76866 [84] valid_0's auc: 0.768468 [85] valid_0's auc: 0.768719 [86] valid_0's auc: 0.768696 [87] valid_0's auc: 0.768676 [88] valid_0's auc: 0.768684 [89] valid_0's auc: 0.768693 [90] valid_0's auc: 0.768666 [91] valid_0's auc: 0.76873 [92] valid_0's auc: 0.768665 [93] valid_0's auc: 0.76916 [94] valid_0's auc: 0.769141 [95] valid_0's auc: 0.769077 [96] valid_0's auc: 0.768722 [97] valid_0's auc: 0.768731 [98] valid_0's auc: 0.769051 [99] valid_0's auc: 0.769084 [100] valid_0's auc: 0.768879 [1] valid_0's auc: 0.748286 [2] valid_0's auc: 0.748286 [3] valid_0's auc: 0.749259 [4] valid_0's auc: 0.749362 [5] valid_0's auc: 0.749362 [6] valid_0's auc: 0.749362 [7] valid_0's auc: 0.749362 [8] valid_0's auc: 0.749483 [9] valid_0's auc: 0.74936 [10] valid_0's auc: 0.749361 [11] valid_0's auc: 0.749362 [12] valid_0's auc: 0.749509 [13] valid_0's auc: 0.757395 [14] valid_0's auc: 0.757131 [15] valid_0's auc: 0.757192 [16] valid_0's auc: 0.757179 [17] valid_0's auc: 0.759842 [18] valid_0's auc: 0.759842 [19] valid_0's auc: 0.759842 [20] valid_0's auc: 0.759842 [21] valid_0's auc: 0.759829 [22] valid_0's auc: 0.759813 [23] valid_0's auc: 0.759844 [24] valid_0's auc: 0.759267 [25] valid_0's auc: 0.760772 [26] valid_0's auc: 0.760956 [27] valid_0's auc: 0.761568 [28] valid_0's auc: 0.762757 [29] valid_0's auc: 0.762609 [30] valid_0's auc: 0.762378 [31] valid_0's auc: 0.762651 [32] valid_0's auc: 0.762598 [33] valid_0's auc: 0.76328 [34] valid_0's auc: 0.7635 [35] valid_0's auc: 0.763434 [36] valid_0's auc: 0.763371 [37] valid_0's auc: 0.763524 [38] valid_0's auc: 0.763325 [39] valid_0's auc: 0.76332 [40] valid_0's auc: 0.763144 [41] valid_0's auc: 0.763069 [42] valid_0's auc: 0.763788 [43] valid_0's auc: 0.764103 [44] valid_0's auc: 0.764047 [45] valid_0's auc: 0.764262 [46] valid_0's auc: 0.764678 [47] valid_0's auc: 0.764708 [48] valid_0's auc: 0.764593 [49] valid_0's auc: 0.765004 [50] valid_0's auc: 0.764929 [51] valid_0's auc: 0.765181 [52] valid_0's auc: 0.766236 [53] valid_0's auc: 0.766075 [54] valid_0's auc: 0.765311 [55] valid_0's auc: 0.766189 [56] valid_0's auc: 0.76613 [57] valid_0's auc: 0.766162 [58] valid_0's auc: 0.766052 [59] valid_0's auc: 0.766053 [60] valid_0's auc: 0.766352 [61] valid_0's auc: 0.766448 [62] valid_0's auc: 0.766314 [63] valid_0's auc: 0.76624 [64] valid_0's auc: 0.766245 [65] valid_0's auc: 0.766094 [66] valid_0's auc: 0.766201 [67] valid_0's auc: 0.766238 [68] valid_0's auc: 0.766368 [69] valid_0's auc: 0.766113 [70] valid_0's auc: 0.766534 [71] valid_0's auc: 0.766537 [72] valid_0's auc: 0.766421 [73] valid_0's auc: 0.766394 [74] valid_0's auc: 0.766421 [75] valid_0's auc: 0.76638 [76] valid_0's auc: 0.766329 [77] valid_0's auc: 0.766692 [78] valid_0's auc: 0.766606 [79] valid_0's auc: 0.766631 [80] valid_0's auc: 0.766506 [81] valid_0's auc: 0.766782 [82] valid_0's auc: 0.766681 [83] valid_0's auc: 0.766804 [84] valid_0's auc: 0.766541 [85] valid_0's auc: 0.767484 [86] valid_0's auc: 0.767418 [87] valid_0's auc: 0.767501 [88] valid_0's auc: 0.767382 [89] valid_0's auc: 0.767382 [90] valid_0's auc: 0.767385 [91] valid_0's auc: 0.767523 [92] valid_0's auc: 0.767353 [93] valid_0's auc: 0.76712 [94] valid_0's auc: 0.767102 [95] valid_0's auc: 0.767498 [96] valid_0's auc: 0.76749 [97] valid_0's auc: 0.767409 [98] valid_0's auc: 0.767268 [99] valid_0's auc: 0.767245 [100] valid_0's auc: 0.76742 [1] valid_0's auc: 0.757043 [2] valid_0's auc: 0.757043 [3] valid_0's auc: 0.757043 [4] valid_0's auc: 0.757043 [5] valid_0's auc: 0.757043 [6] valid_0's auc: 0.757043 [7] valid_0's auc: 0.757043 [8] valid_0's auc: 0.757043 [9] valid_0's auc: 0.757043 [10] valid_0's auc: 0.757043 [11] valid_0's auc: 0.757043 [12] valid_0's auc: 0.757043 [13] valid_0's auc: 0.757043 [14] valid_0's auc: 0.757043 [15] valid_0's auc: 0.757043 [16] valid_0's auc: 0.757043 [17] valid_0's auc: 0.757043 [18] valid_0's auc: 0.757043 [19] valid_0's auc: 0.757043 [20] valid_0's auc: 0.757043 [21] valid_0's auc: 0.757043 [22] valid_0's auc: 0.757043 [23] valid_0's auc: 0.757043 [24] valid_0's auc: 0.758625 [25] valid_0's auc: 0.759423 [26] valid_0's auc: 0.760099 [27] valid_0's auc: 0.760372 [28] valid_0's auc: 0.760721 [29] valid_0's auc: 0.760723 [30] valid_0's auc: 0.760721 [31] valid_0's auc: 0.760638 [32] valid_0's auc: 0.760638 [33] valid_0's auc: 0.760787 [34] valid_0's auc: 0.760774 [35] valid_0's auc: 0.760767 [36] valid_0's auc: 0.760672 [37] valid_0's auc: 0.760837 [38] valid_0's auc: 0.760877 [39] valid_0's auc: 0.760878 [40] valid_0's auc: 0.761056 [41] valid_0's auc: 0.761056 [42] valid_0's auc: 0.760948 [43] valid_0's auc: 0.761049 [44] valid_0's auc: 0.761041 [45] valid_0's auc: 0.760916 [46] valid_0's auc: 0.760889 [47] valid_0's auc: 0.760899 [48] valid_0's auc: 0.760859 [49] valid_0's auc: 0.760945 [50] valid_0's auc: 0.760828 [51] valid_0's auc: 0.760851 [52] valid_0's auc: 0.761384 [53] valid_0's auc: 0.761398 [54] valid_0's auc: 0.761498 [55] valid_0's auc: 0.761464 [56] valid_0's auc: 0.761569 [57] valid_0's auc: 0.761727 [58] valid_0's auc: 0.761733 [59] valid_0's auc: 0.761743 [60] valid_0's auc: 0.761746 [61] valid_0's auc: 0.761744 [62] valid_0's auc: 0.76204 [63] valid_0's auc: 0.762099 [64] valid_0's auc: 0.762097 [65] valid_0's auc: 0.7623 [66] valid_0's auc: 0.762314 [67] valid_0's auc: 0.762316 [68] valid_0's auc: 0.762281 [69] valid_0's auc: 0.762411 [70] valid_0's auc: 0.762074 [71] valid_0's auc: 0.762073 [72] valid_0's auc: 0.762089 [73] valid_0's auc: 0.762087 [74] valid_0's auc: 0.762067 [75] valid_0's auc: 0.762067 [76] valid_0's auc: 0.762115 [77] valid_0's auc: 0.76199 [78] valid_0's auc: 0.762443 [79] valid_0's auc: 0.762179 [80] valid_0's auc: 0.762287 [81] valid_0's auc: 0.762479 [82] valid_0's auc: 0.762476 [83] valid_0's auc: 0.762475 [84] valid_0's auc: 0.762384 [85] valid_0's auc: 0.762212 [86] valid_0's auc: 0.76221 [87] valid_0's auc: 0.76221 [88] valid_0's auc: 0.762148 [89] valid_0's auc: 0.762149 [90] valid_0's auc: 0.762396 [91] valid_0's auc: 0.762631 [92] valid_0's auc: 0.762333 [93] valid_0's auc: 0.762636 [94] valid_0's auc: 0.762636 [95] valid_0's auc: 0.762675 [96] valid_0's auc: 0.762796 [97] valid_0's auc: 0.762798 [98] valid_0's auc: 0.762913 [99] valid_0's auc: 0.762842 [100] valid_0's auc: 0.762814 [1] valid_0's auc: 0.752298 [2] valid_0's auc: 0.759276 [3] valid_0's auc: 0.759067 [4] valid_0's auc: 0.759079 [5] valid_0's auc: 0.759079 [6] valid_0's auc: 0.759532 [7] valid_0's auc: 0.759532 [8] valid_0's auc: 0.760022 [9] valid_0's auc: 0.760088 [10] valid_0's auc: 0.761088 [11] valid_0's auc: 0.76118 [12] valid_0's auc: 0.761204 [13] valid_0's auc: 0.761241 [14] valid_0's auc: 0.761636 [15] valid_0's auc: 0.762392 [16] valid_0's auc: 0.762519 [17] valid_0's auc: 0.762632 [18] valid_0's auc: 0.762461 [19] valid_0's auc: 0.76206 [20] valid_0's auc: 0.76206 [21] valid_0's auc: 0.762252 [22] valid_0's auc: 0.762043 [23] valid_0's auc: 0.762071 [24] valid_0's auc: 0.761918 [25] valid_0's auc: 0.762181 [26] valid_0's auc: 0.762143 [27] valid_0's auc: 0.762652 [28] valid_0's auc: 0.762273 [29] valid_0's auc: 0.762258 [30] valid_0's auc: 0.762682 [31] valid_0's auc: 0.762936 [32] valid_0's auc: 0.762906 [33] valid_0's auc: 0.762494 [34] valid_0's auc: 0.762525 [35] valid_0's auc: 0.763031 [36] valid_0's auc: 0.763035 [37] valid_0's auc: 0.764186 [38] valid_0's auc: 0.764316 [39] valid_0's auc: 0.764316 [40] valid_0's auc: 0.764385 [41] valid_0's auc: 0.764265 [42] valid_0's auc: 0.764223 [43] valid_0's auc: 0.764279 [44] valid_0's auc: 0.764414 [45] valid_0's auc: 0.764437 [46] valid_0's auc: 0.764763 [47] valid_0's auc: 0.764756 [48] valid_0's auc: 0.764393 [49] valid_0's auc: 0.764862 [50] valid_0's auc: 0.764694 [51] valid_0's auc: 0.764903 [52] valid_0's auc: 0.765013 [53] valid_0's auc: 0.765105 [54] valid_0's auc: 0.765277 [55] valid_0's auc: 0.766446 [56] valid_0's auc: 0.766831 [57] valid_0's auc: 0.769933 [58] valid_0's auc: 0.769906 [59] valid_0's auc: 0.769609 [60] valid_0's auc: 0.769994 [61] valid_0's auc: 0.769815 [62] valid_0's auc: 0.770042 [63] valid_0's auc: 0.771214 [64] valid_0's auc: 0.771252 [65] valid_0's auc: 0.771431 [66] valid_0's auc: 0.771427 [67] valid_0's auc: 0.771581 [68] valid_0's auc: 0.771358 [69] valid_0's auc: 0.771738 [70] valid_0's auc: 0.771727 [71] valid_0's auc: 0.771701 [72] valid_0's auc: 0.771878 [73] valid_0's auc: 0.771759 [74] valid_0's auc: 0.77178 [75] valid_0's auc: 0.771755 [76] valid_0's auc: 0.772198 [77] valid_0's auc: 0.772287 [78] valid_0's auc: 0.77261 [79] valid_0's auc: 0.77281 [80] valid_0's auc: 0.77312 [81] valid_0's auc: 0.773289 [82] valid_0's auc: 0.773413 [83] valid_0's auc: 0.773471 [84] valid_0's auc: 0.773488 [85] valid_0's auc: 0.773609 [86] valid_0's auc: 0.773539 [87] valid_0's auc: 0.773566 [88] valid_0's auc: 0.773577 [89] valid_0's auc: 0.773545 [90] valid_0's auc: 0.773541 [91] valid_0's auc: 0.773535 [92] valid_0's auc: 0.773512 [93] valid_0's auc: 0.77355 [94] valid_0's auc: 0.773548 [95] valid_0's auc: 0.774004 [96] valid_0's auc: 0.773721 [97] valid_0's auc: 0.773677 [98] valid_0's auc: 0.774199 [99] valid_0's auc: 0.774101 [100] valid_0's auc: 0.7746 [1] valid_0's auc: 0.754636 [2] valid_0's auc: 0.7683 [3] valid_0's auc: 0.76755 [4] valid_0's auc: 0.771673 [5] valid_0's auc: 0.77165 [6] valid_0's auc: 0.772091 [7] valid_0's auc: 0.772091 [8] valid_0's auc: 0.772132 [9] valid_0's auc: 0.771605 [10] valid_0's auc: 0.770775 [11] valid_0's auc: 0.771277 [12] valid_0's auc: 0.770707 [13] valid_0's auc: 0.771283 [14] valid_0's auc: 0.771711 [15] valid_0's auc: 0.77119 [16] valid_0's auc: 0.771633 [17] valid_0's auc: 0.771584 [18] valid_0's auc: 0.771588 [19] valid_0's auc: 0.771543 [20] valid_0's auc: 0.771543 [21] valid_0's auc: 0.771886 [22] valid_0's auc: 0.7715 [23] valid_0's auc: 0.771517 [24] valid_0's auc: 0.770857 [25] valid_0's auc: 0.771035 [26] valid_0's auc: 0.771912 [27] valid_0's auc: 0.771809 [28] valid_0's auc: 0.77258 [29] valid_0's auc: 0.772955 [30] valid_0's auc: 0.772971 [31] valid_0's auc: 0.772641 [32] valid_0's auc: 0.772611 [33] valid_0's auc: 0.774166 [34] valid_0's auc: 0.774213 [35] valid_0's auc: 0.77425 [36] valid_0's auc: 0.773347 [37] valid_0's auc: 0.772993 [38] valid_0's auc: 0.772906 [39] valid_0's auc: 0.772932 [40] valid_0's auc: 0.773008 [41] valid_0's auc: 0.772858 [42] valid_0's auc: 0.773067 [43] valid_0's auc: 0.773347 [44] valid_0's auc: 0.773352 [45] valid_0's auc: 0.773312 [46] valid_0's auc: 0.773936 [47] valid_0's auc: 0.773849 [48] valid_0's auc: 0.773299 [49] valid_0's auc: 0.773392 [50] valid_0's auc: 0.77455 [51] valid_0's auc: 0.774309 [52] valid_0's auc: 0.774456 [53] valid_0's auc: 0.774478 [54] valid_0's auc: 0.774523 [55] valid_0's auc: 0.774329 [56] valid_0's auc: 0.774536 [57] valid_0's auc: 0.774473 [58] valid_0's auc: 0.774467 [59] valid_0's auc: 0.774537 [60] valid_0's auc: 0.774542 [61] valid_0's auc: 0.774563 [62] valid_0's auc: 0.77455 [63] valid_0's auc: 0.77465 [64] valid_0's auc: 0.774631 [65] valid_0's auc: 0.774766 [66] valid_0's auc: 0.774779 [67] valid_0's auc: 0.774751 [68] valid_0's auc: 0.774863 [69] valid_0's auc: 0.774616 [70] valid_0's auc: 0.774581 [71] valid_0's auc: 0.774516 [72] valid_0's auc: 0.774723 [73] valid_0's auc: 0.77471 [74] valid_0's auc: 0.774703 [75] valid_0's auc: 0.7747 [76] valid_0's auc: 0.774569 [77] valid_0's auc: 0.77472 [78] valid_0's auc: 0.77478 [79] valid_0's auc: 0.77467 [80] valid_0's auc: 0.774905 [81] valid_0's auc: 0.774915 [82] valid_0's auc: 0.774959 [83] valid_0's auc: 0.774998 [84] valid_0's auc: 0.775001 [85] valid_0's auc: 0.775307 [86] valid_0's auc: 0.775288 [87] valid_0's auc: 0.775306 [88] valid_0's auc: 0.775257 [89] valid_0's auc: 0.775222 [90] valid_0's auc: 0.775235 [91] valid_0's auc: 0.775213 [92] valid_0's auc: 0.775292 [93] valid_0's auc: 0.775469 [94] valid_0's auc: 0.775466 [95] valid_0's auc: 0.775585 [96] valid_0's auc: 0.775567 [97] valid_0's auc: 0.775574 [98] valid_0's auc: 0.77562 [99] valid_0's auc: 0.775569 [100] valid_0's auc: 0.775689 [1] valid_0's auc: 0.757698 [2] valid_0's auc: 0.757698 [3] valid_0's auc: 0.758663 [4] valid_0's auc: 0.757968 [5] valid_0's auc: 0.758662 [6] valid_0's auc: 0.75798 [7] valid_0's auc: 0.75798 [8] valid_0's auc: 0.758104 [9] valid_0's auc: 0.757959 [10] valid_0's auc: 0.758427 [11] valid_0's auc: 0.758427 [12] valid_0's auc: 0.758427 [13] valid_0's auc: 0.758433 [14] valid_0's auc: 0.758325 [15] valid_0's auc: 0.758354 [16] valid_0's auc: 0.760319 [17] valid_0's auc: 0.760263 [18] valid_0's auc: 0.760263 [19] valid_0's auc: 0.760263 [20] valid_0's auc: 0.760263 [21] valid_0's auc: 0.760255 [22] valid_0's auc: 0.760736 [23] valid_0's auc: 0.760654 [24] valid_0's auc: 0.760664 [25] valid_0's auc: 0.766487 [26] valid_0's auc: 0.766489 [27] valid_0's auc: 0.766417 [28] valid_0's auc: 0.766308 [29] valid_0's auc: 0.766493 [30] valid_0's auc: 0.76637 [31] valid_0's auc: 0.766556 [32] valid_0's auc: 0.766554 [33] valid_0's auc: 0.766802 [34] valid_0's auc: 0.766753 [35] valid_0's auc: 0.766767 [36] valid_0's auc: 0.76748 [37] valid_0's auc: 0.767074 [38] valid_0's auc: 0.768172 [39] valid_0's auc: 0.767759 [40] valid_0's auc: 0.768357 [41] valid_0's auc: 0.768318 [42] valid_0's auc: 0.768544 [43] valid_0's auc: 0.768559 [44] valid_0's auc: 0.768601 [45] valid_0's auc: 0.768854 [46] valid_0's auc: 0.76941 [47] valid_0's auc: 0.769373 [48] valid_0's auc: 0.769155 [49] valid_0's auc: 0.769244 [50] valid_0's auc: 0.769526 [51] valid_0's auc: 0.76957 [52] valid_0's auc: 0.769874 [53] valid_0's auc: 0.769973 [54] valid_0's auc: 0.769784 [55] valid_0's auc: 0.769842 [56] valid_0's auc: 0.770137 [57] valid_0's auc: 0.770307 [58] valid_0's auc: 0.770308 [59] valid_0's auc: 0.770285 [60] valid_0's auc: 0.769929 [61] valid_0's auc: 0.770009 [62] valid_0's auc: 0.770198 [63] valid_0's auc: 0.770596 [64] valid_0's auc: 0.770676 [65] valid_0's auc: 0.770492 [66] valid_0's auc: 0.770493 [67] valid_0's auc: 0.770469 [68] valid_0's auc: 0.770274 [69] valid_0's auc: 0.770311 [70] valid_0's auc: 0.770581 [71] valid_0's auc: 0.770507 [72] valid_0's auc: 0.770393 [73] valid_0's auc: 0.770362 [74] valid_0's auc: 0.770346 [75] valid_0's auc: 0.770352 [76] valid_0's auc: 0.770722 [77] valid_0's auc: 0.770691 [78] valid_0's auc: 0.770881 [79] valid_0's auc: 0.770734 [80] valid_0's auc: 0.770691 [81] valid_0's auc: 0.77073 [82] valid_0's auc: 0.770836 [83] valid_0's auc: 0.770829 [84] valid_0's auc: 0.771244 [85] valid_0's auc: 0.771144 [86] valid_0's auc: 0.771156 [87] valid_0's auc: 0.771087 [88] valid_0's auc: 0.771085 [89] valid_0's auc: 0.771283 [90] valid_0's auc: 0.771214 [91] valid_0's auc: 0.771206 [92] valid_0's auc: 0.771251 [93] valid_0's auc: 0.77113 [94] valid_0's auc: 0.771272 [95] valid_0's auc: 0.770991 [96] valid_0's auc: 0.771477 [97] valid_0's auc: 0.771409 [98] valid_0's auc: 0.771384 [99] valid_0's auc: 0.771218 [100] valid_0's auc: 0.771661 [1] valid_0's auc: 0.760154 [2] valid_0's auc: 0.760161 [3] valid_0's auc: 0.760248 [4] valid_0's auc: 0.760916 [5] valid_0's auc: 0.760916 [6] valid_0's auc: 0.761004 [7] valid_0's auc: 0.761004 [8] valid_0's auc: 0.761004 [9] valid_0's auc: 0.761194 [10] valid_0's auc: 0.761286 [11] valid_0's auc: 0.761286 [12] valid_0's auc: 0.761286 [13] valid_0's auc: 0.761198 [14] valid_0's auc: 0.761275 [15] valid_0's auc: 0.761194 [16] valid_0's auc: 0.761278 [17] valid_0's auc: 0.761268 [18] valid_0's auc: 0.761268 [19] valid_0's auc: 0.761268 [20] valid_0's auc: 0.761268 [21] valid_0's auc: 0.761268 [22] valid_0's auc: 0.761268 [23] valid_0's auc: 0.761265 [24] valid_0's auc: 0.76137 [25] valid_0's auc: 0.76179 [26] valid_0's auc: 0.76182 [27] valid_0's auc: 0.761936 [28] valid_0's auc: 0.761923 [29] valid_0's auc: 0.761952 [30] valid_0's auc: 0.761943 [31] valid_0's auc: 0.761915 [32] valid_0's auc: 0.761915 [33] valid_0's auc: 0.76199 [34] valid_0's auc: 0.76199 [35] valid_0's auc: 0.76199 [36] valid_0's auc: 0.761954 [37] valid_0's auc: 0.763266 [38] valid_0's auc: 0.763244 [39] valid_0's auc: 0.763254 [40] valid_0's auc: 0.763929 [41] valid_0's auc: 0.763875 [42] valid_0's auc: 0.763886 [43] valid_0's auc: 0.764064 [44] valid_0's auc: 0.764485 [45] valid_0's auc: 0.764143 [46] valid_0's auc: 0.764466 [47] valid_0's auc: 0.764466 [48] valid_0's auc: 0.764681 [49] valid_0's auc: 0.764643 [50] valid_0's auc: 0.764705 [51] valid_0's auc: 0.764722 [52] valid_0's auc: 0.767087 [53] valid_0's auc: 0.767179 [54] valid_0's auc: 0.767144 [55] valid_0's auc: 0.767281 [56] valid_0's auc: 0.767512 [57] valid_0's auc: 0.767443 [58] valid_0's auc: 0.767491 [59] valid_0's auc: 0.76749 [60] valid_0's auc: 0.767484 [61] valid_0's auc: 0.76747 [62] valid_0's auc: 0.767511 [63] valid_0's auc: 0.767614 [64] valid_0's auc: 0.767631 [65] valid_0's auc: 0.767783 [66] valid_0's auc: 0.767704 [67] valid_0's auc: 0.767651 [68] valid_0's auc: 0.767657 [69] valid_0's auc: 0.767636 [70] valid_0's auc: 0.767677 [71] valid_0's auc: 0.767687 [72] valid_0's auc: 0.767681 [73] valid_0's auc: 0.767664 [74] valid_0's auc: 0.767656 [75] valid_0's auc: 0.76765 [76] valid_0's auc: 0.767736 [77] valid_0's auc: 0.767909 [78] valid_0's auc: 0.768071 [79] valid_0's auc: 0.768152 [80] valid_0's auc: 0.768076 [81] valid_0's auc: 0.768155 [82] valid_0's auc: 0.768269 [83] valid_0's auc: 0.768283 [84] valid_0's auc: 0.76829 [85] valid_0's auc: 0.768314 [86] valid_0's auc: 0.768297 [87] valid_0's auc: 0.768305 [88] valid_0's auc: 0.768307 [89] valid_0's auc: 0.76831 [90] valid_0's auc: 0.768319 [91] valid_0's auc: 0.76833 [92] valid_0's auc: 0.768383 [93] valid_0's auc: 0.76835 [94] valid_0's auc: 0.768348 [95] valid_0's auc: 0.768241 [96] valid_0's auc: 0.768246 [97] valid_0's auc: 0.768247 [98] valid_0's auc: 0.768846 [99] valid_0's auc: 0.76882 [100] valid_0's auc: 0.768802 [1] valid_0's auc: 0.759786 [2] valid_0's auc: 0.764657 [3] valid_0's auc: 0.764758 [4] valid_0's auc: 0.764375 [5] valid_0's auc: 0.764375 [6] valid_0's auc: 0.766985 [7] valid_0's auc: 0.766985 [8] valid_0's auc: 0.767017 [9] valid_0's auc: 0.767087 [10] valid_0's auc: 0.767124 [11] valid_0's auc: 0.767094 [12] valid_0's auc: 0.767124 [13] valid_0's auc: 0.768049 [14] valid_0's auc: 0.768137 [15] valid_0's auc: 0.768011 [16] valid_0's auc: 0.768724 [17] valid_0's auc: 0.768589 [18] valid_0's auc: 0.768595 [19] valid_0's auc: 0.768595 [20] valid_0's auc: 0.768595 [21] valid_0's auc: 0.768619 [22] valid_0's auc: 0.768595 [23] valid_0's auc: 0.768595 [24] valid_0's auc: 0.768723 [25] valid_0's auc: 0.768513 [26] valid_0's auc: 0.768403 [27] valid_0's auc: 0.768035 [28] valid_0's auc: 0.768247 [29] valid_0's auc: 0.768126 [30] valid_0's auc: 0.768128 [31] valid_0's auc: 0.768196 [32] valid_0's auc: 0.768173 [33] valid_0's auc: 0.768436 [34] valid_0's auc: 0.76823 [35] valid_0's auc: 0.768254 [36] valid_0's auc: 0.768215 [37] valid_0's auc: 0.768752 [38] valid_0's auc: 0.769168 [39] valid_0's auc: 0.769103 [40] valid_0's auc: 0.769495 [41] valid_0's auc: 0.769406 [42] valid_0's auc: 0.769375 [43] valid_0's auc: 0.769349 [44] valid_0's auc: 0.769347 [45] valid_0's auc: 0.769434 [46] valid_0's auc: 0.769499 [47] valid_0's auc: 0.769453 [48] valid_0's auc: 0.769494 [49] valid_0's auc: 0.769587 [50] valid_0's auc: 0.769778 [51] valid_0's auc: 0.769701 [52] valid_0's auc: 0.769953 [53] valid_0's auc: 0.769821 [54] valid_0's auc: 0.770096 [55] valid_0's auc: 0.77001 [56] valid_0's auc: 0.77088 [57] valid_0's auc: 0.772296 [58] valid_0's auc: 0.772263 [59] valid_0's auc: 0.772162 [60] valid_0's auc: 0.77219 [61] valid_0's auc: 0.772107 [62] valid_0's auc: 0.772749 [63] valid_0's auc: 0.772469 [64] valid_0's auc: 0.772355 [65] valid_0's auc: 0.773286 [66] valid_0's auc: 0.773342 [67] valid_0's auc: 0.773373 [68] valid_0's auc: 0.77344 [69] valid_0's auc: 0.773408 [70] valid_0's auc: 0.773717 [71] valid_0's auc: 0.773612 [72] valid_0's auc: 0.773527 [73] valid_0's auc: 0.773558 [74] valid_0's auc: 0.773404 [75] valid_0's auc: 0.773545 [76] valid_0's auc: 0.773719 [77] valid_0's auc: 0.773939 [78] valid_0's auc: 0.773657 [79] valid_0's auc: 0.774132 [80] valid_0's auc: 0.774251 [81] valid_0's auc: 0.775493 [82] valid_0's auc: 0.775668 [83] valid_0's auc: 0.775637 [84] valid_0's auc: 0.776247 [85] valid_0's auc: 0.776914 [86] valid_0's auc: 0.776719 [87] valid_0's auc: 0.776801 [88] valid_0's auc: 0.776778 [89] valid_0's auc: 0.77678 [90] valid_0's auc: 0.776568 [91] valid_0's auc: 0.776637 [92] valid_0's auc: 0.77673 [93] valid_0's auc: 0.776782 [94] valid_0's auc: 0.776763 [95] valid_0's auc: 0.776884 [96] valid_0's auc: 0.77733 [97] valid_0's auc: 0.777335 [98] valid_0's auc: 0.777751 [99] valid_0's auc: 0.777748 [100] valid_0's auc: 0.778022 [1] valid_0's auc: 0.762215 [2] valid_0's auc: 0.772303 [3] valid_0's auc: 0.772421 [4] valid_0's auc: 0.776396 [5] valid_0's auc: 0.776396 [6] valid_0's auc: 0.776034 [7] valid_0's auc: 0.776034 [8] valid_0's auc: 0.776073 [9] valid_0's auc: 0.775492 [10] valid_0's auc: 0.775158 [11] valid_0's auc: 0.775186 [12] valid_0's auc: 0.775138 [13] valid_0's auc: 0.775428 [14] valid_0's auc: 0.776102 [15] valid_0's auc: 0.776007 [16] valid_0's auc: 0.776659 [17] valid_0's auc: 0.776328 [18] valid_0's auc: 0.776428 [19] valid_0's auc: 0.776702 [20] valid_0's auc: 0.776702 [21] valid_0's auc: 0.776649 [22] valid_0's auc: 0.776457 [23] valid_0's auc: 0.776534 [24] valid_0's auc: 0.77625 [25] valid_0's auc: 0.776649 [26] valid_0's auc: 0.776991 [27] valid_0's auc: 0.77737 [28] valid_0's auc: 0.778308 [29] valid_0's auc: 0.778112 [30] valid_0's auc: 0.778101 [31] valid_0's auc: 0.778954 [32] valid_0's auc: 0.778571 [33] valid_0's auc: 0.778402 [34] valid_0's auc: 0.778444 [35] valid_0's auc: 0.778519 [36] valid_0's auc: 0.779053 [37] valid_0's auc: 0.778855 [38] valid_0's auc: 0.779286 [39] valid_0's auc: 0.77918 [40] valid_0's auc: 0.779893 [41] valid_0's auc: 0.77988 [42] valid_0's auc: 0.779792 [43] valid_0's auc: 0.77996 [44] valid_0's auc: 0.779959 [45] valid_0's auc: 0.779746 [46] valid_0's auc: 0.780106 [47] valid_0's auc: 0.779928 [48] valid_0's auc: 0.779702 [49] valid_0's auc: 0.780486 [50] valid_0's auc: 0.780543 [51] valid_0's auc: 0.780377 [52] valid_0's auc: 0.780245 [53] valid_0's auc: 0.780296 [54] valid_0's auc: 0.780477 [55] valid_0's auc: 0.780359 [56] valid_0's auc: 0.780587 [57] valid_0's auc: 0.780592 [58] valid_0's auc: 0.780519 [59] valid_0's auc: 0.78048 [60] valid_0's auc: 0.78066 [61] valid_0's auc: 0.7806 [62] valid_0's auc: 0.780529 [63] valid_0's auc: 0.780512 [64] valid_0's auc: 0.78051 [65] valid_0's auc: 0.780494 [66] valid_0's auc: 0.780505 [67] valid_0's auc: 0.780639 [68] valid_0's auc: 0.780643 [69] valid_0's auc: 0.781405 [70] valid_0's auc: 0.781379 [71] valid_0's auc: 0.781365 [72] valid_0's auc: 0.78147 [73] valid_0's auc: 0.781439 [74] valid_0's auc: 0.781477 [75] valid_0's auc: 0.78146 [76] valid_0's auc: 0.781614 [77] valid_0's auc: 0.78155 [78] valid_0's auc: 0.781541 [79] valid_0's auc: 0.781483 [80] valid_0's auc: 0.781614 [81] valid_0's auc: 0.781545 [82] valid_0's auc: 0.781525 [83] valid_0's auc: 0.781526 [84] valid_0's auc: 0.781457 [85] valid_0's auc: 0.781331 [86] valid_0's auc: 0.781399 [87] valid_0's auc: 0.781426 [88] valid_0's auc: 0.781474 [89] valid_0's auc: 0.781477 [90] valid_0's auc: 0.781462 [91] valid_0's auc: 0.781498 [92] valid_0's auc: 0.781466 [93] valid_0's auc: 0.781557 [94] valid_0's auc: 0.781488 [95] valid_0's auc: 0.781433 [96] valid_0's auc: 0.781656 [97] valid_0's auc: 0.781655 [98] valid_0's auc: 0.781619 [99] valid_0's auc: 0.781606 [100] valid_0's auc: 0.781655 [1] valid_0's auc: 0.760477 [2] valid_0's auc: 0.760477 [3] valid_0's auc: 0.760477 [4] valid_0's auc: 0.760477 [5] valid_0's auc: 0.760477 [6] valid_0's auc: 0.761103 [7] valid_0's auc: 0.761103 [8] valid_0's auc: 0.76106 [9] valid_0's auc: 0.760922 [10] valid_0's auc: 0.76187 [11] valid_0's auc: 0.761742 [12] valid_0's auc: 0.761742 [13] valid_0's auc: 0.76187 [14] valid_0's auc: 0.761554 [15] valid_0's auc: 0.762118 [16] valid_0's auc: 0.761546 [17] valid_0's auc: 0.762863 [18] valid_0's auc: 0.762864 [19] valid_0's auc: 0.762864 [20] valid_0's auc: 0.762864 [21] valid_0's auc: 0.762727 [22] valid_0's auc: 0.762862 [23] valid_0's auc: 0.76289 [24] valid_0's auc: 0.763555 [25] valid_0's auc: 0.769488 [26] valid_0's auc: 0.76942 [27] valid_0's auc: 0.769341 [28] valid_0's auc: 0.769035 [29] valid_0's auc: 0.769221 [30] valid_0's auc: 0.769021 [31] valid_0's auc: 0.769883 [32] valid_0's auc: 0.769575 [33] valid_0's auc: 0.769276 [34] valid_0's auc: 0.769172 [35] valid_0's auc: 0.769169 [36] valid_0's auc: 0.768997 [37] valid_0's auc: 0.769885 [38] valid_0's auc: 0.770603 [39] valid_0's auc: 0.770569 [40] valid_0's auc: 0.770706 [41] valid_0's auc: 0.770673 [42] valid_0's auc: 0.770714 [43] valid_0's auc: 0.771279 [44] valid_0's auc: 0.771266 [45] valid_0's auc: 0.771327 [46] valid_0's auc: 0.771266 [47] valid_0's auc: 0.771327 [48] valid_0's auc: 0.771392 [49] valid_0's auc: 0.771751 [50] valid_0's auc: 0.771923 [51] valid_0's auc: 0.771944 [52] valid_0's auc: 0.772184 [53] valid_0's auc: 0.772863 [54] valid_0's auc: 0.772887 [55] valid_0's auc: 0.772932 [56] valid_0's auc: 0.7734 [57] valid_0's auc: 0.773666 [58] valid_0's auc: 0.773605 [59] valid_0's auc: 0.773455 [60] valid_0's auc: 0.773439 [61] valid_0's auc: 0.773473 [62] valid_0's auc: 0.773906 [63] valid_0's auc: 0.773854 [64] valid_0's auc: 0.773928 [65] valid_0's auc: 0.773975 [66] valid_0's auc: 0.773847 [67] valid_0's auc: 0.773871 [68] valid_0's auc: 0.773834 [69] valid_0's auc: 0.773791 [70] valid_0's auc: 0.773813 [71] valid_0's auc: 0.773753 [72] valid_0's auc: 0.774121 [73] valid_0's auc: 0.774117 [74] valid_0's auc: 0.774116 [75] valid_0's auc: 0.773973 [76] valid_0's auc: 0.773985 [77] valid_0's auc: 0.773966 [78] valid_0's auc: 0.774442 [79] valid_0's auc: 0.774453 [80] valid_0's auc: 0.774368 [81] valid_0's auc: 0.774675 [82] valid_0's auc: 0.774685 [83] valid_0's auc: 0.774644 [84] valid_0's auc: 0.774938 [85] valid_0's auc: 0.775045 [86] valid_0's auc: 0.775054 [87] valid_0's auc: 0.775045 [88] valid_0's auc: 0.775089 [89] valid_0's auc: 0.775053 [90] valid_0's auc: 0.775075 [91] valid_0's auc: 0.775078 [92] valid_0's auc: 0.774998 [93] valid_0's auc: 0.775079 [94] valid_0's auc: 0.775069 [95] valid_0's auc: 0.775078 [96] valid_0's auc: 0.775271 [97] valid_0's auc: 0.775257 [98] valid_0's auc: 0.77529 [99] valid_0's auc: 0.775282 [100] valid_0's auc: 0.775197 [1] valid_0's auc: 0.7495 [2] valid_0's auc: 0.7495 [3] valid_0's auc: 0.7495 [4] valid_0's auc: 0.7495 [5] valid_0's auc: 0.7495 [6] valid_0's auc: 0.7495 [7] valid_0's auc: 0.7495 [8] valid_0's auc: 0.751338 [9] valid_0's auc: 0.751338 [10] valid_0's auc: 0.751078 [11] valid_0's auc: 0.751078 [12] valid_0's auc: 0.751338 [13] valid_0's auc: 0.751338 [14] valid_0's auc: 0.751338 [15] valid_0's auc: 0.751078 [16] valid_0's auc: 0.751078 [17] valid_0's auc: 0.749299 [18] valid_0's auc: 0.749299 [19] valid_0's auc: 0.749299 [20] valid_0's auc: 0.749299 [21] valid_0's auc: 0.749299 [22] valid_0's auc: 0.751078 [23] valid_0's auc: 0.751078 [24] valid_0's auc: 0.753588 [25] valid_0's auc: 0.753588 [26] valid_0's auc: 0.753588 [27] valid_0's auc: 0.752608 [28] valid_0's auc: 0.752634 [29] valid_0's auc: 0.752634 [30] valid_0's auc: 0.752634 [31] valid_0's auc: 0.753588 [32] valid_0's auc: 0.753588 [33] valid_0's auc: 0.752608 [34] valid_0's auc: 0.752608 [35] valid_0's auc: 0.752634 [36] valid_0's auc: 0.753663 [37] valid_0's auc: 0.753588 [38] valid_0's auc: 0.753817 [39] valid_0's auc: 0.753817 [40] valid_0's auc: 0.753801 [41] valid_0's auc: 0.753622 [42] valid_0's auc: 0.754569 [43] valid_0's auc: 0.754617 [44] valid_0's auc: 0.754617 [45] valid_0's auc: 0.754608 [46] valid_0's auc: 0.754558 [47] valid_0's auc: 0.754558 [48] valid_0's auc: 0.754558 [49] valid_0's auc: 0.754628 [50] valid_0's auc: 0.754558 [51] valid_0's auc: 0.754579 [52] valid_0's auc: 0.754617 [53] valid_0's auc: 0.754621 [54] valid_0's auc: 0.75465 [55] valid_0's auc: 0.756121 [56] valid_0's auc: 0.75612 [57] valid_0's auc: 0.756265 [58] valid_0's auc: 0.756265 [59] valid_0's auc: 0.756265 [60] valid_0's auc: 0.756283 [61] valid_0's auc: 0.756283 [62] valid_0's auc: 0.756245 [63] valid_0's auc: 0.756262 [64] valid_0's auc: 0.756262 [65] valid_0's auc: 0.756285 [66] valid_0's auc: 0.756247 [67] valid_0's auc: 0.756247 [68] valid_0's auc: 0.756285 [69] valid_0's auc: 0.756247 [70] valid_0's auc: 0.756247 [71] valid_0's auc: 0.756247 [72] valid_0's auc: 0.756247 [73] valid_0's auc: 0.756247 [74] valid_0's auc: 0.756247 [75] valid_0's auc: 0.756247 [76] valid_0's auc: 0.756246 [77] valid_0's auc: 0.7563 [78] valid_0's auc: 0.756268 [79] valid_0's auc: 0.756322 [80] valid_0's auc: 0.756322 [81] valid_0's auc: 0.762092 [82] valid_0's auc: 0.762097 [83] valid_0's auc: 0.762082 [84] valid_0's auc: 0.762117 [85] valid_0's auc: 0.762138 [86] valid_0's auc: 0.762142 [87] valid_0's auc: 0.762142 [88] valid_0's auc: 0.762142 [89] valid_0's auc: 0.762133 [90] valid_0's auc: 0.762127 [91] valid_0's auc: 0.762118 [92] valid_0's auc: 0.762166 [93] valid_0's auc: 0.762127 [94] valid_0's auc: 0.762127 [95] valid_0's auc: 0.762173 [96] valid_0's auc: 0.762131 [97] valid_0's auc: 0.762127 [98] valid_0's auc: 0.762461 [99] valid_0's auc: 0.762457 [100] valid_0's auc: 0.762457 [1] valid_0's auc: 0.748453 [2] valid_0's auc: 0.749691 [3] valid_0's auc: 0.751615 [4] valid_0's auc: 0.751094 [5] valid_0's auc: 0.751119 [6] valid_0's auc: 0.752006 [7] valid_0's auc: 0.752006 [8] valid_0's auc: 0.751982 [9] valid_0's auc: 0.752532 [10] valid_0's auc: 0.756575 [11] valid_0's auc: 0.756658 [12] valid_0's auc: 0.756658 [13] valid_0's auc: 0.756638 [14] valid_0's auc: 0.756577 [15] valid_0's auc: 0.756643 [16] valid_0's auc: 0.756819 [17] valid_0's auc: 0.756629 [18] valid_0's auc: 0.756785 [19] valid_0's auc: 0.756519 [20] valid_0's auc: 0.756519 [21] valid_0's auc: 0.756542 [22] valid_0's auc: 0.756415 [23] valid_0's auc: 0.756415 [24] valid_0's auc: 0.756995 [25] valid_0's auc: 0.757296 [26] valid_0's auc: 0.757296 [27] valid_0's auc: 0.756938 [28] valid_0's auc: 0.756638 [29] valid_0's auc: 0.756657 [30] valid_0's auc: 0.756656 [31] valid_0's auc: 0.756939 [32] valid_0's auc: 0.756922 [33] valid_0's auc: 0.756658 [34] valid_0's auc: 0.756658 [35] valid_0's auc: 0.75676 [36] valid_0's auc: 0.756836 [37] valid_0's auc: 0.758193 [38] valid_0's auc: 0.761837 [39] valid_0's auc: 0.761771 [40] valid_0's auc: 0.76182 [41] valid_0's auc: 0.761735 [42] valid_0's auc: 0.762922 [43] valid_0's auc: 0.76256 [44] valid_0's auc: 0.762561 [45] valid_0's auc: 0.762974 [46] valid_0's auc: 0.763946 [47] valid_0's auc: 0.763934 [48] valid_0's auc: 0.765772 [49] valid_0's auc: 0.766153 [50] valid_0's auc: 0.765867 [51] valid_0's auc: 0.766182 [52] valid_0's auc: 0.766029 [53] valid_0's auc: 0.766586 [54] valid_0's auc: 0.766755 [55] valid_0's auc: 0.766879 [56] valid_0's auc: 0.766713 [57] valid_0's auc: 0.76723 [58] valid_0's auc: 0.767224 [59] valid_0's auc: 0.767274 [60] valid_0's auc: 0.76708 [61] valid_0's auc: 0.767084 [62] valid_0's auc: 0.767316 [63] valid_0's auc: 0.768125 [64] valid_0's auc: 0.768149 [65] valid_0's auc: 0.768159 [66] valid_0's auc: 0.768155 [67] valid_0's auc: 0.767995 [68] valid_0's auc: 0.767966 [69] valid_0's auc: 0.768898 [70] valid_0's auc: 0.768752 [71] valid_0's auc: 0.768493 [72] valid_0's auc: 0.768935 [73] valid_0's auc: 0.768953 [74] valid_0's auc: 0.76896 [75] valid_0's auc: 0.768928 [76] valid_0's auc: 0.769088 [77] valid_0's auc: 0.769044 [78] valid_0's auc: 0.769472 [79] valid_0's auc: 0.769704 [80] valid_0's auc: 0.770133 [81] valid_0's auc: 0.770279 [82] valid_0's auc: 0.77036 [83] valid_0's auc: 0.770189 [84] valid_0's auc: 0.770399 [85] valid_0's auc: 0.770458 [86] valid_0's auc: 0.770468 [87] valid_0's auc: 0.770465 [88] valid_0's auc: 0.770445 [89] valid_0's auc: 0.770423 [90] valid_0's auc: 0.770407 [91] valid_0's auc: 0.770374 [92] valid_0's auc: 0.770488 [93] valid_0's auc: 0.770414 [94] valid_0's auc: 0.770352 [95] valid_0's auc: 0.770421 [96] valid_0's auc: 0.770474 [97] valid_0's auc: 0.770517 [98] valid_0's auc: 0.770554 [99] valid_0's auc: 0.770537 [100] valid_0's auc: 0.770578 [1] valid_0's auc: 0.748867 [2] valid_0's auc: 0.762521 [3] valid_0's auc: 0.764062 [4] valid_0's auc: 0.763258 [5] valid_0's auc: 0.763258 [6] valid_0's auc: 0.762373 [7] valid_0's auc: 0.762373 [8] valid_0's auc: 0.762343 [9] valid_0's auc: 0.764046 [10] valid_0's auc: 0.763356 [11] valid_0's auc: 0.763356 [12] valid_0's auc: 0.763956 [13] valid_0's auc: 0.764331 [14] valid_0's auc: 0.763847 [15] valid_0's auc: 0.763082 [16] valid_0's auc: 0.762994 [17] valid_0's auc: 0.763904 [18] valid_0's auc: 0.764023 [19] valid_0's auc: 0.764023 [20] valid_0's auc: 0.764023 [21] valid_0's auc: 0.763919 [22] valid_0's auc: 0.76395 [23] valid_0's auc: 0.763922 [24] valid_0's auc: 0.76392 [25] valid_0's auc: 0.763752 [26] valid_0's auc: 0.764454 [27] valid_0's auc: 0.76508 [28] valid_0's auc: 0.764877 [29] valid_0's auc: 0.764979 [30] valid_0's auc: 0.764998 [31] valid_0's auc: 0.764434 [32] valid_0's auc: 0.764837 [33] valid_0's auc: 0.765323 [34] valid_0's auc: 0.76526 [35] valid_0's auc: 0.765255 [36] valid_0's auc: 0.765941 [37] valid_0's auc: 0.765249 [38] valid_0's auc: 0.766137 [39] valid_0's auc: 0.766162 [40] valid_0's auc: 0.765359 [41] valid_0's auc: 0.76535 [42] valid_0's auc: 0.765736 [43] valid_0's auc: 0.766502 [44] valid_0's auc: 0.766498 [45] valid_0's auc: 0.76613 [46] valid_0's auc: 0.766363 [47] valid_0's auc: 0.766347 [48] valid_0's auc: 0.766244 [49] valid_0's auc: 0.766738 [50] valid_0's auc: 0.766597 [51] valid_0's auc: 0.767732 [52] valid_0's auc: 0.767454 [53] valid_0's auc: 0.767521 [54] valid_0's auc: 0.767431 [55] valid_0's auc: 0.767401 [56] valid_0's auc: 0.768159 [57] valid_0's auc: 0.767965 [58] valid_0's auc: 0.768016 [59] valid_0's auc: 0.767889 [60] valid_0's auc: 0.767804 [61] valid_0's auc: 0.767866 [62] valid_0's auc: 0.768152 [63] valid_0's auc: 0.767838 [64] valid_0's auc: 0.767946 [65] valid_0's auc: 0.767746 [66] valid_0's auc: 0.767741 [67] valid_0's auc: 0.767787 [68] valid_0's auc: 0.767848 [69] valid_0's auc: 0.767646 [70] valid_0's auc: 0.768215 [71] valid_0's auc: 0.768195 [72] valid_0's auc: 0.768186 [73] valid_0's auc: 0.768187 [74] valid_0's auc: 0.768195 [75] valid_0's auc: 0.768135 [76] valid_0's auc: 0.768456 [77] valid_0's auc: 0.768422 [78] valid_0's auc: 0.768505 [79] valid_0's auc: 0.768409 [80] valid_0's auc: 0.768388 [81] valid_0's auc: 0.768728 [82] valid_0's auc: 0.768667 [83] valid_0's auc: 0.76866 [84] valid_0's auc: 0.768468 [85] valid_0's auc: 0.768719 [86] valid_0's auc: 0.768696 [87] valid_0's auc: 0.768676 [88] valid_0's auc: 0.768684 [89] valid_0's auc: 0.768693 [90] valid_0's auc: 0.768666 [91] valid_0's auc: 0.76873 [92] valid_0's auc: 0.768665 [93] valid_0's auc: 0.76916 [94] valid_0's auc: 0.769141 [95] valid_0's auc: 0.769077 [96] valid_0's auc: 0.768722 [97] valid_0's auc: 0.768731 [98] valid_0's auc: 0.769051 [99] valid_0's auc: 0.769084 [100] valid_0's auc: 0.768879 [1] valid_0's auc: 0.748286 [2] valid_0's auc: 0.748286 [3] valid_0's auc: 0.749259 [4] valid_0's auc: 0.749362 [5] valid_0's auc: 0.749362 [6] valid_0's auc: 0.749362 [7] valid_0's auc: 0.749362 [8] valid_0's auc: 0.749483 [9] valid_0's auc: 0.74936 [10] valid_0's auc: 0.749361 [11] valid_0's auc: 0.749362 [12] valid_0's auc: 0.749509 [13] valid_0's auc: 0.757395 [14] valid_0's auc: 0.757131 [15] valid_0's auc: 0.757192 [16] valid_0's auc: 0.757179 [17] valid_0's auc: 0.759842 [18] valid_0's auc: 0.759842 [19] valid_0's auc: 0.759842 [20] valid_0's auc: 0.759842 [21] valid_0's auc: 0.759829 [22] valid_0's auc: 0.759813 [23] valid_0's auc: 0.759844 [24] valid_0's auc: 0.759267 [25] valid_0's auc: 0.760772 [26] valid_0's auc: 0.760956 [27] valid_0's auc: 0.761568 [28] valid_0's auc: 0.762757 [29] valid_0's auc: 0.762609 [30] valid_0's auc: 0.762378 [31] valid_0's auc: 0.762651 [32] valid_0's auc: 0.762598 [33] valid_0's auc: 0.76328 [34] valid_0's auc: 0.7635 [35] valid_0's auc: 0.763434 [36] valid_0's auc: 0.763371 [37] valid_0's auc: 0.763524 [38] valid_0's auc: 0.763325 [39] valid_0's auc: 0.76332 [40] valid_0's auc: 0.763144 [41] valid_0's auc: 0.763069 [42] valid_0's auc: 0.763788 [43] valid_0's auc: 0.764103 [44] valid_0's auc: 0.764047 [45] valid_0's auc: 0.764262 [46] valid_0's auc: 0.764678 [47] valid_0's auc: 0.764708 [48] valid_0's auc: 0.764593 [49] valid_0's auc: 0.765004 [50] valid_0's auc: 0.764929 [51] valid_0's auc: 0.765181 [52] valid_0's auc: 0.766236 [53] valid_0's auc: 0.766075 [54] valid_0's auc: 0.765311 [55] valid_0's auc: 0.766189 [56] valid_0's auc: 0.76613 [57] valid_0's auc: 0.766162 [58] valid_0's auc: 0.766052 [59] valid_0's auc: 0.766053 [60] valid_0's auc: 0.766352 [61] valid_0's auc: 0.766448 [62] valid_0's auc: 0.766314 [63] valid_0's auc: 0.76624 [64] valid_0's auc: 0.766245 [65] valid_0's auc: 0.766094 [66] valid_0's auc: 0.766201 [67] valid_0's auc: 0.766238 [68] valid_0's auc: 0.766368 [69] valid_0's auc: 0.766113 [70] valid_0's auc: 0.766534 [71] valid_0's auc: 0.766537 [72] valid_0's auc: 0.766421 [73] valid_0's auc: 0.766394 [74] valid_0's auc: 0.766421 [75] valid_0's auc: 0.76638 [76] valid_0's auc: 0.766329 [77] valid_0's auc: 0.766692 [78] valid_0's auc: 0.766606 [79] valid_0's auc: 0.766631 [80] valid_0's auc: 0.766506 [81] valid_0's auc: 0.766782 [82] valid_0's auc: 0.766681 [83] valid_0's auc: 0.766804 [84] valid_0's auc: 0.766541 [85] valid_0's auc: 0.767484 [86] valid_0's auc: 0.767418 [87] valid_0's auc: 0.767501 [88] valid_0's auc: 0.767382 [89] valid_0's auc: 0.767382 [90] valid_0's auc: 0.767385 [91] valid_0's auc: 0.767523 [92] valid_0's auc: 0.767353 [93] valid_0's auc: 0.76712 [94] valid_0's auc: 0.767102 [95] valid_0's auc: 0.767498 [96] valid_0's auc: 0.76749 [97] valid_0's auc: 0.767409 [98] valid_0's auc: 0.767268 [99] valid_0's auc: 0.767245 [100] valid_0's auc: 0.76742 [1] valid_0's auc: 0.757043 [2] valid_0's auc: 0.757043 [3] valid_0's auc: 0.757043 [4] valid_0's auc: 0.757043 [5] valid_0's auc: 0.757043 [6] valid_0's auc: 0.757043 [7] valid_0's auc: 0.757043 [8] valid_0's auc: 0.757043 [9] valid_0's auc: 0.757043 [10] valid_0's auc: 0.757043 [11] valid_0's auc: 0.757043 [12] valid_0's auc: 0.757043 [13] valid_0's auc: 0.757043 [14] valid_0's auc: 0.757043 [15] valid_0's auc: 0.757043 [16] valid_0's auc: 0.757043 [17] valid_0's auc: 0.757043 [18] valid_0's auc: 0.757043 [19] valid_0's auc: 0.757043 [20] valid_0's auc: 0.757043 [21] valid_0's auc: 0.757043 [22] valid_0's auc: 0.757043 [23] valid_0's auc: 0.757043 [24] valid_0's auc: 0.758625 [25] valid_0's auc: 0.759423 [26] valid_0's auc: 0.760099 [27] valid_0's auc: 0.760372 [28] valid_0's auc: 0.760721 [29] valid_0's auc: 0.760723 [30] valid_0's auc: 0.760721 [31] valid_0's auc: 0.760638 [32] valid_0's auc: 0.760638 [33] valid_0's auc: 0.760787 [34] valid_0's auc: 0.760774 [35] valid_0's auc: 0.760767 [36] valid_0's auc: 0.760672 [37] valid_0's auc: 0.760837 [38] valid_0's auc: 0.760877 [39] valid_0's auc: 0.760878 [40] valid_0's auc: 0.761056 [41] valid_0's auc: 0.761056 [42] valid_0's auc: 0.760948 [43] valid_0's auc: 0.761049 [44] valid_0's auc: 0.761041 [45] valid_0's auc: 0.760916 [46] valid_0's auc: 0.760889 [47] valid_0's auc: 0.760899 [48] valid_0's auc: 0.760859 [49] valid_0's auc: 0.760945 [50] valid_0's auc: 0.760828 [51] valid_0's auc: 0.760851 [52] valid_0's auc: 0.761384 [53] valid_0's auc: 0.761398 [54] valid_0's auc: 0.761498 [55] valid_0's auc: 0.761464 [56] valid_0's auc: 0.761569 [57] valid_0's auc: 0.761727 [58] valid_0's auc: 0.761733 [59] valid_0's auc: 0.761743 [60] valid_0's auc: 0.761746 [61] valid_0's auc: 0.761744 [62] valid_0's auc: 0.76204 [63] valid_0's auc: 0.762099 [64] valid_0's auc: 0.762097 [65] valid_0's auc: 0.7623 [66] valid_0's auc: 0.762314 [67] valid_0's auc: 0.762316 [68] valid_0's auc: 0.762281 [69] valid_0's auc: 0.762411 [70] valid_0's auc: 0.762074 [71] valid_0's auc: 0.762073 [72] valid_0's auc: 0.762089 [73] valid_0's auc: 0.762087 [74] valid_0's auc: 0.762067 [75] valid_0's auc: 0.762067 [76] valid_0's auc: 0.762115 [77] valid_0's auc: 0.76199 [78] valid_0's auc: 0.762443 [79] valid_0's auc: 0.762179 [80] valid_0's auc: 0.762287 [81] valid_0's auc: 0.762479 [82] valid_0's auc: 0.762476 [83] valid_0's auc: 0.762475 [84] valid_0's auc: 0.762384 [85] valid_0's auc: 0.762212 [86] valid_0's auc: 0.76221 [87] valid_0's auc: 0.76221 [88] valid_0's auc: 0.762148 [89] valid_0's auc: 0.762149 [90] valid_0's auc: 0.762396 [91] valid_0's auc: 0.762631 [92] valid_0's auc: 0.762333 [93] valid_0's auc: 0.762636 [94] valid_0's auc: 0.762636 [95] valid_0's auc: 0.762675 [96] valid_0's auc: 0.762796 [97] valid_0's auc: 0.762798 [98] valid_0's auc: 0.762913 [99] valid_0's auc: 0.762842 [100] valid_0's auc: 0.762814 [1] valid_0's auc: 0.752298 [2] valid_0's auc: 0.759276 [3] valid_0's auc: 0.759067 [4] valid_0's auc: 0.759079 [5] valid_0's auc: 0.759079 [6] valid_0's auc: 0.759532 [7] valid_0's auc: 0.759532 [8] valid_0's auc: 0.760022 [9] valid_0's auc: 0.760088 [10] valid_0's auc: 0.761088 [11] valid_0's auc: 0.76118 [12] valid_0's auc: 0.761204 [13] valid_0's auc: 0.761241 [14] valid_0's auc: 0.761636 [15] valid_0's auc: 0.762392 [16] valid_0's auc: 0.762519 [17] valid_0's auc: 0.762632 [18] valid_0's auc: 0.762461 [19] valid_0's auc: 0.76206 [20] valid_0's auc: 0.76206 [21] valid_0's auc: 0.762252 [22] valid_0's auc: 0.762043 [23] valid_0's auc: 0.762071 [24] valid_0's auc: 0.761918 [25] valid_0's auc: 0.762181 [26] valid_0's auc: 0.762143 [27] valid_0's auc: 0.762652 [28] valid_0's auc: 0.762273 [29] valid_0's auc: 0.762258 [30] valid_0's auc: 0.762682 [31] valid_0's auc: 0.762936 [32] valid_0's auc: 0.762906 [33] valid_0's auc: 0.762494 [34] valid_0's auc: 0.762525 [35] valid_0's auc: 0.763031 [36] valid_0's auc: 0.763035 [37] valid_0's auc: 0.764186 [38] valid_0's auc: 0.764316 [39] valid_0's auc: 0.764316 [40] valid_0's auc: 0.764385 [41] valid_0's auc: 0.764265 [42] valid_0's auc: 0.764223 [43] valid_0's auc: 0.764279 [44] valid_0's auc: 0.764414 [45] valid_0's auc: 0.764437 [46] valid_0's auc: 0.764763 [47] valid_0's auc: 0.764756 [48] valid_0's auc: 0.764393 [49] valid_0's auc: 0.764862 [50] valid_0's auc: 0.764694 [51] valid_0's auc: 0.764903 [52] valid_0's auc: 0.765013 [53] valid_0's auc: 0.765105 [54] valid_0's auc: 0.765277 [55] valid_0's auc: 0.766446 [56] valid_0's auc: 0.766831 [57] valid_0's auc: 0.769933 [58] valid_0's auc: 0.769906 [59] valid_0's auc: 0.769609 [60] valid_0's auc: 0.769994 [61] valid_0's auc: 0.769815 [62] valid_0's auc: 0.770042 [63] valid_0's auc: 0.771214 [64] valid_0's auc: 0.771252 [65] valid_0's auc: 0.771431 [66] valid_0's auc: 0.771427 [67] valid_0's auc: 0.771581 [68] valid_0's auc: 0.771358 [69] valid_0's auc: 0.771738 [70] valid_0's auc: 0.771727 [71] valid_0's auc: 0.771701 [72] valid_0's auc: 0.771878 [73] valid_0's auc: 0.771759 [74] valid_0's auc: 0.77178 [75] valid_0's auc: 0.771755 [76] valid_0's auc: 0.772198 [77] valid_0's auc: 0.772287 [78] valid_0's auc: 0.77261 [79] valid_0's auc: 0.77281 [80] valid_0's auc: 0.77312 [81] valid_0's auc: 0.773289 [82] valid_0's auc: 0.773413 [83] valid_0's auc: 0.773471 [84] valid_0's auc: 0.773488 [85] valid_0's auc: 0.773609 [86] valid_0's auc: 0.773539 [87] valid_0's auc: 0.773566 [88] valid_0's auc: 0.773577 [89] valid_0's auc: 0.773545 [90] valid_0's auc: 0.773541 [91] valid_0's auc: 0.773535 [92] valid_0's auc: 0.773512 [93] valid_0's auc: 0.77355 [94] valid_0's auc: 0.773548 [95] valid_0's auc: 0.774004 [96] valid_0's auc: 0.773721 [97] valid_0's auc: 0.773677 [98] valid_0's auc: 0.774199 [99] valid_0's auc: 0.774101 [100] valid_0's auc: 0.7746 [1] valid_0's auc: 0.754636 [2] valid_0's auc: 0.7683 [3] valid_0's auc: 0.76755 [4] valid_0's auc: 0.771673 [5] valid_0's auc: 0.77165 [6] valid_0's auc: 0.772091 [7] valid_0's auc: 0.772091 [8] valid_0's auc: 0.772132 [9] valid_0's auc: 0.771605 [10] valid_0's auc: 0.770775 [11] valid_0's auc: 0.771277 [12] valid_0's auc: 0.770707 [13] valid_0's auc: 0.771283 [14] valid_0's auc: 0.771711 [15] valid_0's auc: 0.77119 [16] valid_0's auc: 0.771633 [17] valid_0's auc: 0.771584 [18] valid_0's auc: 0.771588 [19] valid_0's auc: 0.771543 [20] valid_0's auc: 0.771543 [21] valid_0's auc: 0.771886 [22] valid_0's auc: 0.7715 [23] valid_0's auc: 0.771517 [24] valid_0's auc: 0.770857 [25] valid_0's auc: 0.771035 [26] valid_0's auc: 0.771912 [27] valid_0's auc: 0.771809 [28] valid_0's auc: 0.77258 [29] valid_0's auc: 0.772955 [30] valid_0's auc: 0.772971 [31] valid_0's auc: 0.772641 [32] valid_0's auc: 0.772611 [33] valid_0's auc: 0.774166 [34] valid_0's auc: 0.774213 [35] valid_0's auc: 0.77425 [36] valid_0's auc: 0.773347 [37] valid_0's auc: 0.772993 [38] valid_0's auc: 0.772906 [39] valid_0's auc: 0.772932 [40] valid_0's auc: 0.773008 [41] valid_0's auc: 0.772858 [42] valid_0's auc: 0.773067 [43] valid_0's auc: 0.773347 [44] valid_0's auc: 0.773352 [45] valid_0's auc: 0.773312 [46] valid_0's auc: 0.773936 [47] valid_0's auc: 0.773849 [48] valid_0's auc: 0.773299 [49] valid_0's auc: 0.773392 [50] valid_0's auc: 0.77455 [51] valid_0's auc: 0.774309 [52] valid_0's auc: 0.774456 [53] valid_0's auc: 0.774478 [54] valid_0's auc: 0.774523 [55] valid_0's auc: 0.774329 [56] valid_0's auc: 0.774536 [57] valid_0's auc: 0.774473 [58] valid_0's auc: 0.774467 [59] valid_0's auc: 0.774537 [60] valid_0's auc: 0.774542 [61] valid_0's auc: 0.774563 [62] valid_0's auc: 0.77455 [63] valid_0's auc: 0.77465 [64] valid_0's auc: 0.774631 [65] valid_0's auc: 0.774766 [66] valid_0's auc: 0.774779 [67] valid_0's auc: 0.774751 [68] valid_0's auc: 0.774863 [69] valid_0's auc: 0.774616 [70] valid_0's auc: 0.774581 [71] valid_0's auc: 0.774516 [72] valid_0's auc: 0.774723 [73] valid_0's auc: 0.77471 [74] valid_0's auc: 0.774703 [75] valid_0's auc: 0.7747 [76] valid_0's auc: 0.774569 [77] valid_0's auc: 0.77472 [78] valid_0's auc: 0.77478 [79] valid_0's auc: 0.77467 [80] valid_0's auc: 0.774905 [81] valid_0's auc: 0.774915 [82] valid_0's auc: 0.774959 [83] valid_0's auc: 0.774998 [84] valid_0's auc: 0.775001 [85] valid_0's auc: 0.775307 [86] valid_0's auc: 0.775288 [87] valid_0's auc: 0.775306 [88] valid_0's auc: 0.775257 [89] valid_0's auc: 0.775222 [90] valid_0's auc: 0.775235 [91] valid_0's auc: 0.775213 [92] valid_0's auc: 0.775292 [93] valid_0's auc: 0.775469 [94] valid_0's auc: 0.775466 [95] valid_0's auc: 0.775585 [96] valid_0's auc: 0.775567 [97] valid_0's auc: 0.775574 [98] valid_0's auc: 0.77562 [99] valid_0's auc: 0.775569 [100] valid_0's auc: 0.775689 [1] valid_0's auc: 0.757698 [2] valid_0's auc: 0.757698 [3] valid_0's auc: 0.758663 [4] valid_0's auc: 0.757968 [5] valid_0's auc: 0.758662 [6] valid_0's auc: 0.75798 [7] valid_0's auc: 0.75798 [8] valid_0's auc: 0.758104 [9] valid_0's auc: 0.757959 [10] valid_0's auc: 0.758427 [11] valid_0's auc: 0.758427 [12] valid_0's auc: 0.758427 [13] valid_0's auc: 0.758433 [14] valid_0's auc: 0.758325 [15] valid_0's auc: 0.758354 [16] valid_0's auc: 0.760319 [17] valid_0's auc: 0.760263 [18] valid_0's auc: 0.760263 [19] valid_0's auc: 0.760263 [20] valid_0's auc: 0.760263 [21] valid_0's auc: 0.760255 [22] valid_0's auc: 0.760736 [23] valid_0's auc: 0.760654 [24] valid_0's auc: 0.760664 [25] valid_0's auc: 0.766487 [26] valid_0's auc: 0.766489 [27] valid_0's auc: 0.766417 [28] valid_0's auc: 0.766308 [29] valid_0's auc: 0.766493 [30] valid_0's auc: 0.76637 [31] valid_0's auc: 0.766556 [32] valid_0's auc: 0.766554 [33] valid_0's auc: 0.766802 [34] valid_0's auc: 0.766753 [35] valid_0's auc: 0.766767 [36] valid_0's auc: 0.76748 [37] valid_0's auc: 0.767074 [38] valid_0's auc: 0.768172 [39] valid_0's auc: 0.767759 [40] valid_0's auc: 0.768357 [41] valid_0's auc: 0.768318 [42] valid_0's auc: 0.768544 [43] valid_0's auc: 0.768559 [44] valid_0's auc: 0.768601 [45] valid_0's auc: 0.768854 [46] valid_0's auc: 0.76941 [47] valid_0's auc: 0.769373 [48] valid_0's auc: 0.769155 [49] valid_0's auc: 0.769244 [50] valid_0's auc: 0.769526 [51] valid_0's auc: 0.76957 [52] valid_0's auc: 0.769874 [53] valid_0's auc: 0.769973 [54] valid_0's auc: 0.769784 [55] valid_0's auc: 0.769842 [56] valid_0's auc: 0.770137 [57] valid_0's auc: 0.770307 [58] valid_0's auc: 0.770308 [59] valid_0's auc: 0.770285 [60] valid_0's auc: 0.769929 [61] valid_0's auc: 0.770009 [62] valid_0's auc: 0.770198 [63] valid_0's auc: 0.770596 [64] valid_0's auc: 0.770676 [65] valid_0's auc: 0.770492 [66] valid_0's auc: 0.770493 [67] valid_0's auc: 0.770469 [68] valid_0's auc: 0.770274 [69] valid_0's auc: 0.770311 [70] valid_0's auc: 0.770581 [71] valid_0's auc: 0.770507 [72] valid_0's auc: 0.770393 [73] valid_0's auc: 0.770362 [74] valid_0's auc: 0.770346 [75] valid_0's auc: 0.770352 [76] valid_0's auc: 0.770722 [77] valid_0's auc: 0.770691 [78] valid_0's auc: 0.770881 [79] valid_0's auc: 0.770734 [80] valid_0's auc: 0.770691 [81] valid_0's auc: 0.77073 [82] valid_0's auc: 0.770836 [83] valid_0's auc: 0.770829 [84] valid_0's auc: 0.771244 [85] valid_0's auc: 0.771144 [86] valid_0's auc: 0.771156 [87] valid_0's auc: 0.771087 [88] valid_0's auc: 0.771085 [89] valid_0's auc: 0.771283 [90] valid_0's auc: 0.771214 [91] valid_0's auc: 0.771206 [92] valid_0's auc: 0.771251 [93] valid_0's auc: 0.77113 [94] valid_0's auc: 0.771272 [95] valid_0's auc: 0.770991 [96] valid_0's auc: 0.771477 [97] valid_0's auc: 0.771409 [98] valid_0's auc: 0.771384 [99] valid_0's auc: 0.771218 [100] valid_0's auc: 0.771661 [1] valid_0's auc: 0.760154 [2] valid_0's auc: 0.760161 [3] valid_0's auc: 0.760248 [4] valid_0's auc: 0.760916 [5] valid_0's auc: 0.760916 [6] valid_0's auc: 0.761004 [7] valid_0's auc: 0.761004 [8] valid_0's auc: 0.761004 [9] valid_0's auc: 0.761194 [10] valid_0's auc: 0.761286 [11] valid_0's auc: 0.761286 [12] valid_0's auc: 0.761286 [13] valid_0's auc: 0.761198 [14] valid_0's auc: 0.761275 [15] valid_0's auc: 0.761194 [16] valid_0's auc: 0.761278 [17] valid_0's auc: 0.761268 [18] valid_0's auc: 0.761268 [19] valid_0's auc: 0.761268 [20] valid_0's auc: 0.761268 [21] valid_0's auc: 0.761268 [22] valid_0's auc: 0.761268 [23] valid_0's auc: 0.761265 [24] valid_0's auc: 0.76137 [25] valid_0's auc: 0.76179 [26] valid_0's auc: 0.76182 [27] valid_0's auc: 0.761936 [28] valid_0's auc: 0.761923 [29] valid_0's auc: 0.761952 [30] valid_0's auc: 0.761943 [31] valid_0's auc: 0.761915 [32] valid_0's auc: 0.761915 [33] valid_0's auc: 0.76199 [34] valid_0's auc: 0.76199 [35] valid_0's auc: 0.76199 [36] valid_0's auc: 0.761954 [37] valid_0's auc: 0.763266 [38] valid_0's auc: 0.763244 [39] valid_0's auc: 0.763254 [40] valid_0's auc: 0.763929 [41] valid_0's auc: 0.763875 [42] valid_0's auc: 0.763886 [43] valid_0's auc: 0.764064 [44] valid_0's auc: 0.764485 [45] valid_0's auc: 0.764143 [46] valid_0's auc: 0.764466 [47] valid_0's auc: 0.764466 [48] valid_0's auc: 0.764681 [49] valid_0's auc: 0.764643 [50] valid_0's auc: 0.764705 [51] valid_0's auc: 0.764722 [52] valid_0's auc: 0.767087 [53] valid_0's auc: 0.767179 [54] valid_0's auc: 0.767144 [55] valid_0's auc: 0.767281 [56] valid_0's auc: 0.767512 [57] valid_0's auc: 0.767443 [58] valid_0's auc: 0.767491 [59] valid_0's auc: 0.76749 [60] valid_0's auc: 0.767484 [61] valid_0's auc: 0.76747 [62] valid_0's auc: 0.767511 [63] valid_0's auc: 0.767614 [64] valid_0's auc: 0.767631 [65] valid_0's auc: 0.767783 [66] valid_0's auc: 0.767704 [67] valid_0's auc: 0.767651 [68] valid_0's auc: 0.767657 [69] valid_0's auc: 0.767636 [70] valid_0's auc: 0.767677 [71] valid_0's auc: 0.767687 [72] valid_0's auc: 0.767681 [73] valid_0's auc: 0.767664 [74] valid_0's auc: 0.767656 [75] valid_0's auc: 0.76765 [76] valid_0's auc: 0.767736 [77] valid_0's auc: 0.767909 [78] valid_0's auc: 0.768071 [79] valid_0's auc: 0.768152 [80] valid_0's auc: 0.768076 [81] valid_0's auc: 0.768155 [82] valid_0's auc: 0.768269 [83] valid_0's auc: 0.768283 [84] valid_0's auc: 0.76829 [85] valid_0's auc: 0.768314 [86] valid_0's auc: 0.768297 [87] valid_0's auc: 0.768305 [88] valid_0's auc: 0.768307 [89] valid_0's auc: 0.76831 [90] valid_0's auc: 0.768319 [91] valid_0's auc: 0.76833 [92] valid_0's auc: 0.768383 [93] valid_0's auc: 0.76835 [94] valid_0's auc: 0.768348 [95] valid_0's auc: 0.768241 [96] valid_0's auc: 0.768246 [97] valid_0's auc: 0.768247 [98] valid_0's auc: 0.768846 [99] valid_0's auc: 0.76882 [100] valid_0's auc: 0.768802 [1] valid_0's auc: 0.759786 [2] valid_0's auc: 0.764657 [3] valid_0's auc: 0.764758 [4] valid_0's auc: 0.764375 [5] valid_0's auc: 0.764375 [6] valid_0's auc: 0.766985 [7] valid_0's auc: 0.766985 [8] valid_0's auc: 0.767017 [9] valid_0's auc: 0.767087 [10] valid_0's auc: 0.767124 [11] valid_0's auc: 0.767094 [12] valid_0's auc: 0.767124 [13] valid_0's auc: 0.768049 [14] valid_0's auc: 0.768137 [15] valid_0's auc: 0.768011 [16] valid_0's auc: 0.768724 [17] valid_0's auc: 0.768589 [18] valid_0's auc: 0.768595 [19] valid_0's auc: 0.768595 [20] valid_0's auc: 0.768595 [21] valid_0's auc: 0.768619 [22] valid_0's auc: 0.768595 [23] valid_0's auc: 0.768595 [24] valid_0's auc: 0.768723 [25] valid_0's auc: 0.768513 [26] valid_0's auc: 0.768403 [27] valid_0's auc: 0.768035 [28] valid_0's auc: 0.768247 [29] valid_0's auc: 0.768126 [30] valid_0's auc: 0.768128 [31] valid_0's auc: 0.768196 [32] valid_0's auc: 0.768173 [33] valid_0's auc: 0.768436 [34] valid_0's auc: 0.76823 [35] valid_0's auc: 0.768254 [36] valid_0's auc: 0.768215 [37] valid_0's auc: 0.768752 [38] valid_0's auc: 0.769168 [39] valid_0's auc: 0.769103 [40] valid_0's auc: 0.769495 [41] valid_0's auc: 0.769406 [42] valid_0's auc: 0.769375 [43] valid_0's auc: 0.769349 [44] valid_0's auc: 0.769347 [45] valid_0's auc: 0.769434 [46] valid_0's auc: 0.769499 [47] valid_0's auc: 0.769453 [48] valid_0's auc: 0.769494 [49] valid_0's auc: 0.769587 [50] valid_0's auc: 0.769778 [51] valid_0's auc: 0.769701 [52] valid_0's auc: 0.769953 [53] valid_0's auc: 0.769821 [54] valid_0's auc: 0.770096 [55] valid_0's auc: 0.77001 [56] valid_0's auc: 0.77088 [57] valid_0's auc: 0.772296 [58] valid_0's auc: 0.772263 [59] valid_0's auc: 0.772162 [60] valid_0's auc: 0.77219 [61] valid_0's auc: 0.772107 [62] valid_0's auc: 0.772749 [63] valid_0's auc: 0.772469 [64] valid_0's auc: 0.772355 [65] valid_0's auc: 0.773286 [66] valid_0's auc: 0.773342 [67] valid_0's auc: 0.773373 [68] valid_0's auc: 0.77344 [69] valid_0's auc: 0.773408 [70] valid_0's auc: 0.773717 [71] valid_0's auc: 0.773612 [72] valid_0's auc: 0.773527 [73] valid_0's auc: 0.773558 [74] valid_0's auc: 0.773404 [75] valid_0's auc: 0.773545 [76] valid_0's auc: 0.773719 [77] valid_0's auc: 0.773939 [78] valid_0's auc: 0.773657 [79] valid_0's auc: 0.774132 [80] valid_0's auc: 0.774251 [81] valid_0's auc: 0.775493 [82] valid_0's auc: 0.775668 [83] valid_0's auc: 0.775637 [84] valid_0's auc: 0.776247 [85] valid_0's auc: 0.776914 [86] valid_0's auc: 0.776719 [87] valid_0's auc: 0.776801 [88] valid_0's auc: 0.776778 [89] valid_0's auc: 0.77678 [90] valid_0's auc: 0.776568 [91] valid_0's auc: 0.776637 [92] valid_0's auc: 0.77673 [93] valid_0's auc: 0.776782 [94] valid_0's auc: 0.776763 [95] valid_0's auc: 0.776884 [96] valid_0's auc: 0.77733 [97] valid_0's auc: 0.777335 [98] valid_0's auc: 0.777751 [99] valid_0's auc: 0.777748 [100] valid_0's auc: 0.778022 [1] valid_0's auc: 0.762215 [2] valid_0's auc: 0.772303 [3] valid_0's auc: 0.772421 [4] valid_0's auc: 0.776396 [5] valid_0's auc: 0.776396 [6] valid_0's auc: 0.776034 [7] valid_0's auc: 0.776034 [8] valid_0's auc: 0.776073 [9] valid_0's auc: 0.775492 [10] valid_0's auc: 0.775158 [11] valid_0's auc: 0.775186 [12] valid_0's auc: 0.775138 [13] valid_0's auc: 0.775428 [14] valid_0's auc: 0.776102 [15] valid_0's auc: 0.776007 [16] valid_0's auc: 0.776659 [17] valid_0's auc: 0.776328 [18] valid_0's auc: 0.776428 [19] valid_0's auc: 0.776702 [20] valid_0's auc: 0.776702 [21] valid_0's auc: 0.776649 [22] valid_0's auc: 0.776457 [23] valid_0's auc: 0.776534 [24] valid_0's auc: 0.77625 [25] valid_0's auc: 0.776649 [26] valid_0's auc: 0.776991 [27] valid_0's auc: 0.77737 [28] valid_0's auc: 0.778308 [29] valid_0's auc: 0.778112 [30] valid_0's auc: 0.778101 [31] valid_0's auc: 0.778954 [32] valid_0's auc: 0.778571 [33] valid_0's auc: 0.778402 [34] valid_0's auc: 0.778444 [35] valid_0's auc: 0.778519 [36] valid_0's auc: 0.779053 [37] valid_0's auc: 0.778855 [38] valid_0's auc: 0.779286 [39] valid_0's auc: 0.77918 [40] valid_0's auc: 0.779893 [41] valid_0's auc: 0.77988 [42] valid_0's auc: 0.779792 [43] valid_0's auc: 0.77996 [44] valid_0's auc: 0.779959 [45] valid_0's auc: 0.779746 [46] valid_0's auc: 0.780106 [47] valid_0's auc: 0.779928 [48] valid_0's auc: 0.779702 [49] valid_0's auc: 0.780486 [50] valid_0's auc: 0.780543 [51] valid_0's auc: 0.780377 [52] valid_0's auc: 0.780245 [53] valid_0's auc: 0.780296 [54] valid_0's auc: 0.780477 [55] valid_0's auc: 0.780359 [56] valid_0's auc: 0.780587 [57] valid_0's auc: 0.780592 [58] valid_0's auc: 0.780519 [59] valid_0's auc: 0.78048 [60] valid_0's auc: 0.78066 [61] valid_0's auc: 0.7806 [62] valid_0's auc: 0.780529 [63] valid_0's auc: 0.780512 [64] valid_0's auc: 0.78051 [65] valid_0's auc: 0.780494 [66] valid_0's auc: 0.780505 [67] valid_0's auc: 0.780639 [68] valid_0's auc: 0.780643 [69] valid_0's auc: 0.781405 [70] valid_0's auc: 0.781379 [71] valid_0's auc: 0.781365 [72] valid_0's auc: 0.78147 [73] valid_0's auc: 0.781439 [74] valid_0's auc: 0.781477 [75] valid_0's auc: 0.78146 [76] valid_0's auc: 0.781614 [77] valid_0's auc: 0.78155 [78] valid_0's auc: 0.781541 [79] valid_0's auc: 0.781483 [80] valid_0's auc: 0.781614 [81] valid_0's auc: 0.781545 [82] valid_0's auc: 0.781525 [83] valid_0's auc: 0.781526 [84] valid_0's auc: 0.781457 [85] valid_0's auc: 0.781331 [86] valid_0's auc: 0.781399 [87] valid_0's auc: 0.781426 [88] valid_0's auc: 0.781474 [89] valid_0's auc: 0.781477 [90] valid_0's auc: 0.781462 [91] valid_0's auc: 0.781498 [92] valid_0's auc: 0.781466 [93] valid_0's auc: 0.781557 [94] valid_0's auc: 0.781488 [95] valid_0's auc: 0.781433 [96] valid_0's auc: 0.781656 [97] valid_0's auc: 0.781655 [98] valid_0's auc: 0.781619 [99] valid_0's auc: 0.781606 [100] valid_0's auc: 0.781655 [1] valid_0's auc: 0.760477 [2] valid_0's auc: 0.760477 [3] valid_0's auc: 0.760477 [4] valid_0's auc: 0.760477 [5] valid_0's auc: 0.760477 [6] valid_0's auc: 0.761103 [7] valid_0's auc: 0.761103 [8] valid_0's auc: 0.76106 [9] valid_0's auc: 0.760922 [10] valid_0's auc: 0.76187 [11] valid_0's auc: 0.761742 [12] valid_0's auc: 0.761742 [13] valid_0's auc: 0.76187 [14] valid_0's auc: 0.761554 [15] valid_0's auc: 0.762118 [16] valid_0's auc: 0.761546 [17] valid_0's auc: 0.762863 [18] valid_0's auc: 0.762864 [19] valid_0's auc: 0.762864 [20] valid_0's auc: 0.762864 [21] valid_0's auc: 0.762727 [22] valid_0's auc: 0.762862 [23] valid_0's auc: 0.76289 [24] valid_0's auc: 0.763555 [25] valid_0's auc: 0.769488 [26] valid_0's auc: 0.76942 [27] valid_0's auc: 0.769341 [28] valid_0's auc: 0.769035 [29] valid_0's auc: 0.769221 [30] valid_0's auc: 0.769021 [31] valid_0's auc: 0.769883 [32] valid_0's auc: 0.769575 [33] valid_0's auc: 0.769276 [34] valid_0's auc: 0.769172 [35] valid_0's auc: 0.769169 [36] valid_0's auc: 0.768997 [37] valid_0's auc: 0.769885 [38] valid_0's auc: 0.770603 [39] valid_0's auc: 0.770569 [40] valid_0's auc: 0.770706 [41] valid_0's auc: 0.770673 [42] valid_0's auc: 0.770714 [43] valid_0's auc: 0.771279 [44] valid_0's auc: 0.771266 [45] valid_0's auc: 0.771327 [46] valid_0's auc: 0.771266 [47] valid_0's auc: 0.771327 [48] valid_0's auc: 0.771392 [49] valid_0's auc: 0.771751 [50] valid_0's auc: 0.771923 [51] valid_0's auc: 0.771944 [52] valid_0's auc: 0.772184 [53] valid_0's auc: 0.772863 [54] valid_0's auc: 0.772887 [55] valid_0's auc: 0.772932 [56] valid_0's auc: 0.7734 [57] valid_0's auc: 0.773666 [58] valid_0's auc: 0.773605 [59] valid_0's auc: 0.773455 [60] valid_0's auc: 0.773439 [61] valid_0's auc: 0.773473 [62] valid_0's auc: 0.773906 [63] valid_0's auc: 0.773854 [64] valid_0's auc: 0.773928 [65] valid_0's auc: 0.773975 [66] valid_0's auc: 0.773847 [67] valid_0's auc: 0.773871 [68] valid_0's auc: 0.773834 [69] valid_0's auc: 0.773791 [70] valid_0's auc: 0.773813 [71] valid_0's auc: 0.773753 [72] valid_0's auc: 0.774121 [73] valid_0's auc: 0.774117 [74] valid_0's auc: 0.774116 [75] valid_0's auc: 0.773973 [76] valid_0's auc: 0.773985 [77] valid_0's auc: 0.773966 [78] valid_0's auc: 0.774442 [79] valid_0's auc: 0.774453 [80] valid_0's auc: 0.774368 [81] valid_0's auc: 0.774675 [82] valid_0's auc: 0.774685 [83] valid_0's auc: 0.774644 [84] valid_0's auc: 0.774938 [85] valid_0's auc: 0.775045 [86] valid_0's auc: 0.775054 [87] valid_0's auc: 0.775045 [88] valid_0's auc: 0.775089 [89] valid_0's auc: 0.775053 [90] valid_0's auc: 0.775075 [91] valid_0's auc: 0.775078 [92] valid_0's auc: 0.774998 [93] valid_0's auc: 0.775079 [94] valid_0's auc: 0.775069 [95] valid_0's auc: 0.775078 [96] valid_0's auc: 0.775271 [97] valid_0's auc: 0.775257 [98] valid_0's auc: 0.77529 [99] valid_0's auc: 0.775282 [100] valid_0's auc: 0.775197 [1] valid_0's auc: 0.7495 [2] valid_0's auc: 0.7495 [3] valid_0's auc: 0.7495 [4] valid_0's auc: 0.751338 [5] valid_0's auc: 0.751338 [6] valid_0's auc: 0.750327 [7] valid_0's auc: 0.750327 [8] valid_0's auc: 0.750327 [9] valid_0's auc: 0.753589 [10] valid_0's auc: 0.751663 [11] valid_0's auc: 0.751663 [12] valid_0's auc: 0.751663 [13] valid_0's auc: 0.753629 [14] valid_0's auc: 0.751667 [15] valid_0's auc: 0.753799 [16] valid_0's auc: 0.75409 [17] valid_0's auc: 0.75437 [18] valid_0's auc: 0.754555 [19] valid_0's auc: 0.754555 [20] valid_0's auc: 0.75437 [21] valid_0's auc: 0.75454 [22] valid_0's auc: 0.754536 [23] valid_0's auc: 0.754532 [24] valid_0's auc: 0.754602 [25] valid_0's auc: 0.760514 [26] valid_0's auc: 0.760553 [27] valid_0's auc: 0.760625 [28] valid_0's auc: 0.76055 [29] valid_0's auc: 0.760601 [30] valid_0's auc: 0.760469 [31] valid_0's auc: 0.76243 [32] valid_0's auc: 0.762366 [33] valid_0's auc: 0.76231 [34] valid_0's auc: 0.762278 [35] valid_0's auc: 0.762393 [36] valid_0's auc: 0.762182 [37] valid_0's auc: 0.762012 [38] valid_0's auc: 0.762041 [39] valid_0's auc: 0.762299 [40] valid_0's auc: 0.762127 [41] valid_0's auc: 0.762302 [42] valid_0's auc: 0.762337 [43] valid_0's auc: 0.76231 [44] valid_0's auc: 0.762147 [45] valid_0's auc: 0.76238 [46] valid_0's auc: 0.762362 [47] valid_0's auc: 0.7624 [48] valid_0's auc: 0.762364 [49] valid_0's auc: 0.762933 [50] valid_0's auc: 0.763672 [51] valid_0's auc: 0.764058 [52] valid_0's auc: 0.764455 [53] valid_0's auc: 0.764269 [54] valid_0's auc: 0.766175 [55] valid_0's auc: 0.766913 [56] valid_0's auc: 0.767065 [57] valid_0's auc: 0.766834 [58] valid_0's auc: 0.766894 [59] valid_0's auc: 0.766915 [60] valid_0's auc: 0.766971 [61] valid_0's auc: 0.766952 [62] valid_0's auc: 0.767665 [63] valid_0's auc: 0.767655 [64] valid_0's auc: 0.767635 [65] valid_0's auc: 0.767597 [66] valid_0's auc: 0.767546 [67] valid_0's auc: 0.767567 [68] valid_0's auc: 0.76756 [69] valid_0's auc: 0.767479 [70] valid_0's auc: 0.767496 [71] valid_0's auc: 0.7675 [72] valid_0's auc: 0.767763 [73] valid_0's auc: 0.768087 [74] valid_0's auc: 0.76767 [75] valid_0's auc: 0.76772 [76] valid_0's auc: 0.767691 [77] valid_0's auc: 0.767619 [78] valid_0's auc: 0.767665 [79] valid_0's auc: 0.768263 [80] valid_0's auc: 0.768021 [81] valid_0's auc: 0.768156 [82] valid_0's auc: 0.769091 [83] valid_0's auc: 0.769085 [84] valid_0's auc: 0.769005 [85] valid_0's auc: 0.769298 [86] valid_0's auc: 0.769249 [87] valid_0's auc: 0.769219 [88] valid_0's auc: 0.769183 [89] valid_0's auc: 0.769129 [90] valid_0's auc: 0.769701 [91] valid_0's auc: 0.769705 [92] valid_0's auc: 0.769733 [93] valid_0's auc: 0.769842 [94] valid_0's auc: 0.769559 [95] valid_0's auc: 0.769506 [96] valid_0's auc: 0.769805 [97] valid_0's auc: 0.769775 [98] valid_0's auc: 0.769843 [99] valid_0's auc: 0.769828 [100] valid_0's auc: 0.769725 [1] valid_0's auc: 0.748453 [2] valid_0's auc: 0.750923 [3] valid_0's auc: 0.75159 [4] valid_0's auc: 0.752015 [5] valid_0's auc: 0.756456 [6] valid_0's auc: 0.757053 [7] valid_0's auc: 0.757053 [8] valid_0's auc: 0.757245 [9] valid_0's auc: 0.756643 [10] valid_0's auc: 0.756789 [11] valid_0's auc: 0.756791 [12] valid_0's auc: 0.757546 [13] valid_0's auc: 0.757041 [14] valid_0's auc: 0.757916 [15] valid_0's auc: 0.758323 [16] valid_0's auc: 0.762649 [17] valid_0's auc: 0.763888 [18] valid_0's auc: 0.763851 [19] valid_0's auc: 0.7643 [20] valid_0's auc: 0.7643 [21] valid_0's auc: 0.764526 [22] valid_0's auc: 0.765621 [23] valid_0's auc: 0.765736 [24] valid_0's auc: 0.765354 [25] valid_0's auc: 0.765948 [26] valid_0's auc: 0.765554 [27] valid_0's auc: 0.767708 [28] valid_0's auc: 0.768403 [29] valid_0's auc: 0.768837 [30] valid_0's auc: 0.767932 [31] valid_0's auc: 0.769135 [32] valid_0's auc: 0.768762 [33] valid_0's auc: 0.769205 [34] valid_0's auc: 0.769184 [35] valid_0's auc: 0.769103 [36] valid_0's auc: 0.769351 [37] valid_0's auc: 0.769706 [38] valid_0's auc: 0.770011 [39] valid_0's auc: 0.769793 [40] valid_0's auc: 0.769716 [41] valid_0's auc: 0.769734 [42] valid_0's auc: 0.769777 [43] valid_0's auc: 0.769948 [44] valid_0's auc: 0.769965 [45] valid_0's auc: 0.769943 [46] valid_0's auc: 0.770255 [47] valid_0's auc: 0.770166 [48] valid_0's auc: 0.770441 [49] valid_0's auc: 0.770272 [50] valid_0's auc: 0.77048 [51] valid_0's auc: 0.770307 [52] valid_0's auc: 0.77023 [53] valid_0's auc: 0.770333 [54] valid_0's auc: 0.770719 [55] valid_0's auc: 0.770651 [56] valid_0's auc: 0.770888 [57] valid_0's auc: 0.770661 [58] valid_0's auc: 0.770679 [59] valid_0's auc: 0.770734 [60] valid_0's auc: 0.770969 [61] valid_0's auc: 0.770957 [62] valid_0's auc: 0.770821 [63] valid_0's auc: 0.770921 [64] valid_0's auc: 0.77134 [65] valid_0's auc: 0.771506 [66] valid_0's auc: 0.771477 [67] valid_0's auc: 0.771467 [68] valid_0's auc: 0.771463 [69] valid_0's auc: 0.771513 [70] valid_0's auc: 0.771571 [71] valid_0's auc: 0.77151 [72] valid_0's auc: 0.77134 [73] valid_0's auc: 0.771352 [74] valid_0's auc: 0.771424 [75] valid_0's auc: 0.771336 [76] valid_0's auc: 0.771164 [77] valid_0's auc: 0.771425 [78] valid_0's auc: 0.771437 [79] valid_0's auc: 0.771328 [80] valid_0's auc: 0.771823 [81] valid_0's auc: 0.771911 [82] valid_0's auc: 0.771851 [83] valid_0's auc: 0.771943 [84] valid_0's auc: 0.77203 [85] valid_0's auc: 0.771763 [86] valid_0's auc: 0.771761 [87] valid_0's auc: 0.771757 [88] valid_0's auc: 0.771803 [89] valid_0's auc: 0.77181 [90] valid_0's auc: 0.771788 [91] valid_0's auc: 0.771799 [92] valid_0's auc: 0.771791 [93] valid_0's auc: 0.772506 [94] valid_0's auc: 0.772504 [95] valid_0's auc: 0.772567 [96] valid_0's auc: 0.7724 [97] valid_0's auc: 0.772422 [98] valid_0's auc: 0.772325 [99] valid_0's auc: 0.77207 [100] valid_0's auc: 0.772598 [1] valid_0's auc: 0.748867 [2] valid_0's auc: 0.764626 [3] valid_0's auc: 0.764062 [4] valid_0's auc: 0.763174 [5] valid_0's auc: 0.763174 [6] valid_0's auc: 0.762373 [7] valid_0's auc: 0.762373 [8] valid_0's auc: 0.762362 [9] valid_0's auc: 0.76208 [10] valid_0's auc: 0.764271 [11] valid_0's auc: 0.764385 [12] valid_0's auc: 0.764821 [13] valid_0's auc: 0.765442 [14] valid_0's auc: 0.765184 [15] valid_0's auc: 0.765028 [16] valid_0's auc: 0.764415 [17] valid_0's auc: 0.765623 [18] valid_0's auc: 0.766556 [19] valid_0's auc: 0.766645 [20] valid_0's auc: 0.766614 [21] valid_0's auc: 0.766746 [22] valid_0's auc: 0.7666 [23] valid_0's auc: 0.7666 [24] valid_0's auc: 0.76649 [25] valid_0's auc: 0.767107 [26] valid_0's auc: 0.767174 [27] valid_0's auc: 0.768623 [28] valid_0's auc: 0.768909 [29] valid_0's auc: 0.768838 [30] valid_0's auc: 0.768888 [31] valid_0's auc: 0.768729 [32] valid_0's auc: 0.768839 [33] valid_0's auc: 0.76912 [34] valid_0's auc: 0.769078 [35] valid_0's auc: 0.76903 [36] valid_0's auc: 0.768857 [37] valid_0's auc: 0.768625 [38] valid_0's auc: 0.769566 [39] valid_0's auc: 0.769595 [40] valid_0's auc: 0.769485 [41] valid_0's auc: 0.769462 [42] valid_0's auc: 0.769607 [43] valid_0's auc: 0.769984 [44] valid_0's auc: 0.77014 [45] valid_0's auc: 0.769858 [46] valid_0's auc: 0.770436 [47] valid_0's auc: 0.770434 [48] valid_0's auc: 0.770289 [49] valid_0's auc: 0.770654 [50] valid_0's auc: 0.769558 [51] valid_0's auc: 0.769724 [52] valid_0's auc: 0.769717 [53] valid_0's auc: 0.76963 [54] valid_0's auc: 0.770038 [55] valid_0's auc: 0.771136 [56] valid_0's auc: 0.771297 [57] valid_0's auc: 0.771245 [58] valid_0's auc: 0.771251 [59] valid_0's auc: 0.771149 [60] valid_0's auc: 0.77153 [61] valid_0's auc: 0.77158 [62] valid_0's auc: 0.771379 [63] valid_0's auc: 0.771845 [64] valid_0's auc: 0.771886 [65] valid_0's auc: 0.771767 [66] valid_0's auc: 0.77168 [67] valid_0's auc: 0.771708 [68] valid_0's auc: 0.771782 [69] valid_0's auc: 0.771657 [70] valid_0's auc: 0.771589 [71] valid_0's auc: 0.771596 [72] valid_0's auc: 0.771916 [73] valid_0's auc: 0.771913 [74] valid_0's auc: 0.771938 [75] valid_0's auc: 0.77189 [76] valid_0's auc: 0.771804 [77] valid_0's auc: 0.771921 [78] valid_0's auc: 0.772233 [79] valid_0's auc: 0.772134 [80] valid_0's auc: 0.772308 [81] valid_0's auc: 0.772456 [82] valid_0's auc: 0.772534 [83] valid_0's auc: 0.772563 [84] valid_0's auc: 0.77248 [85] valid_0's auc: 0.773027 [86] valid_0's auc: 0.773028 [87] valid_0's auc: 0.773038 [88] valid_0's auc: 0.773018 [89] valid_0's auc: 0.773081 [90] valid_0's auc: 0.773037 [91] valid_0's auc: 0.77304 [92] valid_0's auc: 0.773228 [93] valid_0's auc: 0.773083 [94] valid_0's auc: 0.77306 [95] valid_0's auc: 0.773082 [96] valid_0's auc: 0.773302 [97] valid_0's auc: 0.773207 [98] valid_0's auc: 0.773282 [99] valid_0's auc: 0.773215 [100] valid_0's auc: 0.773306 [1] valid_0's auc: 0.748286 [2] valid_0's auc: 0.748643 [3] valid_0's auc: 0.748974 [4] valid_0's auc: 0.749498 [5] valid_0's auc: 0.749498 [6] valid_0's auc: 0.7492 [7] valid_0's auc: 0.7492 [8] valid_0's auc: 0.752539 [9] valid_0's auc: 0.762203 [10] valid_0's auc: 0.762197 [11] valid_0's auc: 0.762188 [12] valid_0's auc: 0.762281 [13] valid_0's auc: 0.762658 [14] valid_0's auc: 0.762467 [15] valid_0's auc: 0.764294 [16] valid_0's auc: 0.765254 [17] valid_0's auc: 0.765911 [18] valid_0's auc: 0.765918 [19] valid_0's auc: 0.765884 [20] valid_0's auc: 0.765884 [21] valid_0's auc: 0.76579 [22] valid_0's auc: 0.765663 [23] valid_0's auc: 0.76566 [24] valid_0's auc: 0.765605 [25] valid_0's auc: 0.766181 [26] valid_0's auc: 0.766276 [27] valid_0's auc: 0.76655 [28] valid_0's auc: 0.766088 [29] valid_0's auc: 0.766655 [30] valid_0's auc: 0.766075 [31] valid_0's auc: 0.767689 [32] valid_0's auc: 0.767668 [33] valid_0's auc: 0.767533 [34] valid_0's auc: 0.767118 [35] valid_0's auc: 0.767054 [36] valid_0's auc: 0.766499 [37] valid_0's auc: 0.767457 [38] valid_0's auc: 0.767132 [39] valid_0's auc: 0.76716 [40] valid_0's auc: 0.767097 [41] valid_0's auc: 0.766949 [42] valid_0's auc: 0.76775 [43] valid_0's auc: 0.768144 [44] valid_0's auc: 0.768126 [45] valid_0's auc: 0.767837 [46] valid_0's auc: 0.768498 [47] valid_0's auc: 0.768361 [48] valid_0's auc: 0.768177 [49] valid_0's auc: 0.768134 [50] valid_0's auc: 0.768357 [51] valid_0's auc: 0.768274 [52] valid_0's auc: 0.768282 [53] valid_0's auc: 0.769519 [54] valid_0's auc: 0.769432 [55] valid_0's auc: 0.769116 [56] valid_0's auc: 0.769951 [57] valid_0's auc: 0.769814 [58] valid_0's auc: 0.769683 [59] valid_0's auc: 0.769728 [60] valid_0's auc: 0.769657 [61] valid_0's auc: 0.769657 [62] valid_0's auc: 0.770357 [63] valid_0's auc: 0.770351 [64] valid_0's auc: 0.770457 [65] valid_0's auc: 0.770513 [66] valid_0's auc: 0.770786 [67] valid_0's auc: 0.770685 [68] valid_0's auc: 0.770703 [69] valid_0's auc: 0.770468 [70] valid_0's auc: 0.770401 [71] valid_0's auc: 0.770392 [72] valid_0's auc: 0.770924 [73] valid_0's auc: 0.770897 [74] valid_0's auc: 0.770976 [75] valid_0's auc: 0.770904 [76] valid_0's auc: 0.770828 [77] valid_0's auc: 0.770694 [78] valid_0's auc: 0.771128 [79] valid_0's auc: 0.770851 [80] valid_0's auc: 0.770718 [81] valid_0's auc: 0.771544 [82] valid_0's auc: 0.771195 [83] valid_0's auc: 0.771197 [84] valid_0's auc: 0.771199 [85] valid_0's auc: 0.77162 [86] valid_0's auc: 0.771434 [87] valid_0's auc: 0.771354 [88] valid_0's auc: 0.771411 [89] valid_0's auc: 0.771386 [90] valid_0's auc: 0.771444 [91] valid_0's auc: 0.771538 [92] valid_0's auc: 0.771342 [93] valid_0's auc: 0.771303 [94] valid_0's auc: 0.771238 [95] valid_0's auc: 0.771726 [96] valid_0's auc: 0.771687 [97] valid_0's auc: 0.771616 [98] valid_0's auc: 0.771642 [99] valid_0's auc: 0.771567 [100] valid_0's auc: 0.771987 [1] valid_0's auc: 0.757043 [2] valid_0's auc: 0.757043 [3] valid_0's auc: 0.757043 [4] valid_0's auc: 0.757043 [5] valid_0's auc: 0.757043 [6] valid_0's auc: 0.757043 [7] valid_0's auc: 0.757043 [8] valid_0's auc: 0.757043 [9] valid_0's auc: 0.758795 [10] valid_0's auc: 0.760475 [11] valid_0's auc: 0.760597 [12] valid_0's auc: 0.760584 [13] valid_0's auc: 0.760681 [14] valid_0's auc: 0.760683 [15] valid_0's auc: 0.76056 [16] valid_0's auc: 0.761402 [17] valid_0's auc: 0.761529 [18] valid_0's auc: 0.761529 [19] valid_0's auc: 0.761591 [20] valid_0's auc: 0.761595 [21] valid_0's auc: 0.761558 [22] valid_0's auc: 0.761546 [23] valid_0's auc: 0.761522 [24] valid_0's auc: 0.761983 [25] valid_0's auc: 0.762505 [26] valid_0's auc: 0.762508 [27] valid_0's auc: 0.761965 [28] valid_0's auc: 0.762515 [29] valid_0's auc: 0.762438 [30] valid_0's auc: 0.761944 [31] valid_0's auc: 0.762352 [32] valid_0's auc: 0.762362 [33] valid_0's auc: 0.76204 [34] valid_0's auc: 0.762014 [35] valid_0's auc: 0.762034 [36] valid_0's auc: 0.762299 [37] valid_0's auc: 0.76202 [38] valid_0's auc: 0.762389 [39] valid_0's auc: 0.762389 [40] valid_0's auc: 0.76257 [41] valid_0's auc: 0.762487 [42] valid_0's auc: 0.768379 [43] valid_0's auc: 0.768593 [44] valid_0's auc: 0.768641 [45] valid_0's auc: 0.76864 [46] valid_0's auc: 0.768701 [47] valid_0's auc: 0.768685 [48] valid_0's auc: 0.768725 [49] valid_0's auc: 0.76878 [50] valid_0's auc: 0.768815 [51] valid_0's auc: 0.768899 [52] valid_0's auc: 0.769356 [53] valid_0's auc: 0.76957 [54] valid_0's auc: 0.769592 [55] valid_0's auc: 0.770163 [56] valid_0's auc: 0.770087 [57] valid_0's auc: 0.769987 [58] valid_0's auc: 0.770034 [59] valid_0's auc: 0.770034 [60] valid_0's auc: 0.770112 [61] valid_0's auc: 0.770101 [62] valid_0's auc: 0.77021 [63] valid_0's auc: 0.770568 [64] valid_0's auc: 0.770577 [65] valid_0's auc: 0.770507 [66] valid_0's auc: 0.770555 [67] valid_0's auc: 0.770527 [68] valid_0's auc: 0.770536 [69] valid_0's auc: 0.770528 [70] valid_0's auc: 0.770708 [71] valid_0's auc: 0.770806 [72] valid_0's auc: 0.770551 [73] valid_0's auc: 0.770486 [74] valid_0's auc: 0.770564 [75] valid_0's auc: 0.770553 [76] valid_0's auc: 0.770568 [77] valid_0's auc: 0.771518 [78] valid_0's auc: 0.772063 [79] valid_0's auc: 0.772278 [80] valid_0's auc: 0.772168 [81] valid_0's auc: 0.772335 [82] valid_0's auc: 0.772699 [83] valid_0's auc: 0.772683 [84] valid_0's auc: 0.772628 [85] valid_0's auc: 0.772676 [86] valid_0's auc: 0.772657 [87] valid_0's auc: 0.772683 [88] valid_0's auc: 0.772761 [89] valid_0's auc: 0.772677 [90] valid_0's auc: 0.772599 [91] valid_0's auc: 0.772597 [92] valid_0's auc: 0.772742 [93] valid_0's auc: 0.772798 [94] valid_0's auc: 0.772787 [95] valid_0's auc: 0.772724 [96] valid_0's auc: 0.773257 [97] valid_0's auc: 0.773116 [98] valid_0's auc: 0.773239 [99] valid_0's auc: 0.773173 [100] valid_0's auc: 0.772973 [1] valid_0's auc: 0.752298 [2] valid_0's auc: 0.759276 [3] valid_0's auc: 0.759067 [4] valid_0's auc: 0.760567 [5] valid_0's auc: 0.760567 [6] valid_0's auc: 0.759938 [7] valid_0's auc: 0.759938 [8] valid_0's auc: 0.760226 [9] valid_0's auc: 0.762248 [10] valid_0's auc: 0.76367 [11] valid_0's auc: 0.763621 [12] valid_0's auc: 0.763836 [13] valid_0's auc: 0.764138 [14] valid_0's auc: 0.763808 [15] valid_0's auc: 0.763779 [16] valid_0's auc: 0.764396 [17] valid_0's auc: 0.76465 [18] valid_0's auc: 0.764675 [19] valid_0's auc: 0.764672 [20] valid_0's auc: 0.764672 [21] valid_0's auc: 0.764679 [22] valid_0's auc: 0.764654 [23] valid_0's auc: 0.764654 [24] valid_0's auc: 0.764862 [25] valid_0's auc: 0.767665 [26] valid_0's auc: 0.767657 [27] valid_0's auc: 0.76752 [28] valid_0's auc: 0.768079 [29] valid_0's auc: 0.767723 [30] valid_0's auc: 0.767753 [31] valid_0's auc: 0.767904 [32] valid_0's auc: 0.767735 [33] valid_0's auc: 0.767987 [34] valid_0's auc: 0.767913 [35] valid_0's auc: 0.767958 [36] valid_0's auc: 0.767726 [37] valid_0's auc: 0.77144 [38] valid_0's auc: 0.771983 [39] valid_0's auc: 0.772072 [40] valid_0's auc: 0.772642 [41] valid_0's auc: 0.7724 [42] valid_0's auc: 0.772606 [43] valid_0's auc: 0.773112 [44] valid_0's auc: 0.773262 [45] valid_0's auc: 0.773283 [46] valid_0's auc: 0.7736 [47] valid_0's auc: 0.773597 [48] valid_0's auc: 0.774146 [49] valid_0's auc: 0.77475 [50] valid_0's auc: 0.775632 [51] valid_0's auc: 0.775868 [52] valid_0's auc: 0.776302 [53] valid_0's auc: 0.776677 [54] valid_0's auc: 0.776795 [55] valid_0's auc: 0.777018 [56] valid_0's auc: 0.776968 [57] valid_0's auc: 0.7774 [58] valid_0's auc: 0.77728 [59] valid_0's auc: 0.777279 [60] valid_0's auc: 0.777589 [61] valid_0's auc: 0.777624 [62] valid_0's auc: 0.777569 [63] valid_0's auc: 0.777958 [64] valid_0's auc: 0.778038 [65] valid_0's auc: 0.777877 [66] valid_0's auc: 0.777922 [67] valid_0's auc: 0.777913 [68] valid_0's auc: 0.777988 [69] valid_0's auc: 0.778129 [70] valid_0's auc: 0.778129 [71] valid_0's auc: 0.778101 [72] valid_0's auc: 0.778072 [73] valid_0's auc: 0.778109 [74] valid_0's auc: 0.778116 [75] valid_0's auc: 0.778077 [76] valid_0's auc: 0.778073 [77] valid_0's auc: 0.778366 [78] valid_0's auc: 0.778557 [79] valid_0's auc: 0.778774 [80] valid_0's auc: 0.778649 [81] valid_0's auc: 0.778791 [82] valid_0's auc: 0.779486 [83] valid_0's auc: 0.779434 [84] valid_0's auc: 0.779476 [85] valid_0's auc: 0.779434 [86] valid_0's auc: 0.779464 [87] valid_0's auc: 0.779465 [88] valid_0's auc: 0.779408 [89] valid_0's auc: 0.779419 [90] valid_0's auc: 0.779439 [91] valid_0's auc: 0.779496 [92] valid_0's auc: 0.779354 [93] valid_0's auc: 0.779674 [94] valid_0's auc: 0.779704 [95] valid_0's auc: 0.779594 [96] valid_0's auc: 0.779564 [97] valid_0's auc: 0.779641 [98] valid_0's auc: 0.779724 [99] valid_0's auc: 0.779738 [100] valid_0's auc: 0.779794 [1] valid_0's auc: 0.754636 [2] valid_0's auc: 0.768299 [3] valid_0's auc: 0.771575 [4] valid_0's auc: 0.770665 [5] valid_0's auc: 0.770665 [6] valid_0's auc: 0.772371 [7] valid_0's auc: 0.772371 [8] valid_0's auc: 0.772084 [9] valid_0's auc: 0.771631 [10] valid_0's auc: 0.771184 [11] valid_0's auc: 0.771361 [12] valid_0's auc: 0.771364 [13] valid_0's auc: 0.771236 [14] valid_0's auc: 0.77209 [15] valid_0's auc: 0.771527 [16] valid_0's auc: 0.773395 [17] valid_0's auc: 0.772813 [18] valid_0's auc: 0.772593 [19] valid_0's auc: 0.772593 [20] valid_0's auc: 0.772593 [21] valid_0's auc: 0.772756 [22] valid_0's auc: 0.772602 [23] valid_0's auc: 0.77261 [24] valid_0's auc: 0.772405 [25] valid_0's auc: 0.772337 [26] valid_0's auc: 0.773139 [27] valid_0's auc: 0.774044 [28] valid_0's auc: 0.774584 [29] valid_0's auc: 0.774653 [30] valid_0's auc: 0.774633 [31] valid_0's auc: 0.775546 [32] valid_0's auc: 0.775245 [33] valid_0's auc: 0.775 [34] valid_0's auc: 0.774977 [35] valid_0's auc: 0.774951 [36] valid_0's auc: 0.774779 [37] valid_0's auc: 0.774521 [38] valid_0's auc: 0.775045 [39] valid_0's auc: 0.775058 [40] valid_0's auc: 0.774883 [41] valid_0's auc: 0.774926 [42] valid_0's auc: 0.775126 [43] valid_0's auc: 0.775779 [44] valid_0's auc: 0.77582 [45] valid_0's auc: 0.775998 [46] valid_0's auc: 0.775977 [47] valid_0's auc: 0.775857 [48] valid_0's auc: 0.775963 [49] valid_0's auc: 0.77571 [50] valid_0's auc: 0.77598 [51] valid_0's auc: 0.776138 [52] valid_0's auc: 0.776229 [53] valid_0's auc: 0.776544 [54] valid_0's auc: 0.777067 [55] valid_0's auc: 0.776815 [56] valid_0's auc: 0.776867 [57] valid_0's auc: 0.777088 [58] valid_0's auc: 0.77714 [59] valid_0's auc: 0.777164 [60] valid_0's auc: 0.777809 [61] valid_0's auc: 0.777681 [62] valid_0's auc: 0.777586 [63] valid_0's auc: 0.777788 [64] valid_0's auc: 0.777767 [65] valid_0's auc: 0.778097 [66] valid_0's auc: 0.77814 [67] valid_0's auc: 0.778187 [68] valid_0's auc: 0.778159 [69] valid_0's auc: 0.778054 [70] valid_0's auc: 0.778241 [71] valid_0's auc: 0.778186 [72] valid_0's auc: 0.778181 [73] valid_0's auc: 0.778076 [74] valid_0's auc: 0.778134 [75] valid_0's auc: 0.778119 [76] valid_0's auc: 0.778214 [77] valid_0's auc: 0.778572 [78] valid_0's auc: 0.779137 [79] valid_0's auc: 0.778959 [80] valid_0's auc: 0.77866 [81] valid_0's auc: 0.779315 [82] valid_0's auc: 0.779205 [83] valid_0's auc: 0.77921 [84] valid_0's auc: 0.779256 [85] valid_0's auc: 0.778944 [86] valid_0's auc: 0.778859 [87] valid_0's auc: 0.77897 [88] valid_0's auc: 0.779201 [89] valid_0's auc: 0.779222 [90] valid_0's auc: 0.779197 [91] valid_0's auc: 0.779267 [92] valid_0's auc: 0.778952 [93] valid_0's auc: 0.778946 [94] valid_0's auc: 0.778927 [95] valid_0's auc: 0.779292 [96] valid_0's auc: 0.77937 [97] valid_0's auc: 0.779374 [98] valid_0's auc: 0.779003 [99] valid_0's auc: 0.779013 [100] valid_0's auc: 0.778886 [1] valid_0's auc: 0.757698 [2] valid_0's auc: 0.757948 [3] valid_0's auc: 0.758047 [4] valid_0's auc: 0.758753 [5] valid_0's auc: 0.758732 [6] valid_0's auc: 0.761583 [7] valid_0's auc: 0.761583 [8] valid_0's auc: 0.761034 [9] valid_0's auc: 0.762049 [10] valid_0's auc: 0.762074 [11] valid_0's auc: 0.762198 [12] valid_0's auc: 0.762199 [13] valid_0's auc: 0.767967 [14] valid_0's auc: 0.767981 [15] valid_0's auc: 0.767899 [16] valid_0's auc: 0.767954 [17] valid_0's auc: 0.769467 [18] valid_0's auc: 0.769501 [19] valid_0's auc: 0.769247 [20] valid_0's auc: 0.769247 [21] valid_0's auc: 0.769322 [22] valid_0's auc: 0.769347 [23] valid_0's auc: 0.769282 [24] valid_0's auc: 0.769233 [25] valid_0's auc: 0.769509 [26] valid_0's auc: 0.769618 [27] valid_0's auc: 0.770013 [28] valid_0's auc: 0.770055 [29] valid_0's auc: 0.770067 [30] valid_0's auc: 0.76999 [31] valid_0's auc: 0.770295 [32] valid_0's auc: 0.770246 [33] valid_0's auc: 0.770121 [34] valid_0's auc: 0.770037 [35] valid_0's auc: 0.770074 [36] valid_0's auc: 0.770297 [37] valid_0's auc: 0.77025 [38] valid_0's auc: 0.77052 [39] valid_0's auc: 0.770531 [40] valid_0's auc: 0.770241 [41] valid_0's auc: 0.770249 [42] valid_0's auc: 0.770513 [43] valid_0's auc: 0.771491 [44] valid_0's auc: 0.771462 [45] valid_0's auc: 0.771853 [46] valid_0's auc: 0.771821 [47] valid_0's auc: 0.771835 [48] valid_0's auc: 0.772956 [49] valid_0's auc: 0.772811 [50] valid_0's auc: 0.772768 [51] valid_0's auc: 0.773013 [52] valid_0's auc: 0.773168 [53] valid_0's auc: 0.772969 [54] valid_0's auc: 0.773559 [55] valid_0's auc: 0.773395 [56] valid_0's auc: 0.773962 [57] valid_0's auc: 0.773393 [58] valid_0's auc: 0.773411 [59] valid_0's auc: 0.773418 [60] valid_0's auc: 0.773612 [61] valid_0's auc: 0.773587 [62] valid_0's auc: 0.774549 [63] valid_0's auc: 0.775026 [64] valid_0's auc: 0.775062 [65] valid_0's auc: 0.775142 [66] valid_0's auc: 0.775147 [67] valid_0's auc: 0.775173 [68] valid_0's auc: 0.775176 [69] valid_0's auc: 0.774918 [70] valid_0's auc: 0.775034 [71] valid_0's auc: 0.77502 [72] valid_0's auc: 0.775638 [73] valid_0's auc: 0.775681 [74] valid_0's auc: 0.775659 [75] valid_0's auc: 0.775646 [76] valid_0's auc: 0.775464 [77] valid_0's auc: 0.775468 [78] valid_0's auc: 0.776185 [79] valid_0's auc: 0.776177 [80] valid_0's auc: 0.776149 [81] valid_0's auc: 0.776095 [82] valid_0's auc: 0.77591 [83] valid_0's auc: 0.77598 [84] valid_0's auc: 0.77593 [85] valid_0's auc: 0.776513 [86] valid_0's auc: 0.776489 [87] valid_0's auc: 0.776508 [88] valid_0's auc: 0.776496 [89] valid_0's auc: 0.776483 [90] valid_0's auc: 0.776364 [91] valid_0's auc: 0.776394 [92] valid_0's auc: 0.776189 [93] valid_0's auc: 0.776245 [94] valid_0's auc: 0.776325 [95] valid_0's auc: 0.776434 [96] valid_0's auc: 0.776475 [97] valid_0's auc: 0.776512 [98] valid_0's auc: 0.776745 [99] valid_0's auc: 0.776682 [100] valid_0's auc: 0.776691 [1] valid_0's auc: 0.760154 [2] valid_0's auc: 0.760161 [3] valid_0's auc: 0.761275 [4] valid_0's auc: 0.761194 [5] valid_0's auc: 0.761194 [6] valid_0's auc: 0.761366 [7] valid_0's auc: 0.761366 [8] valid_0's auc: 0.761278 [9] valid_0's auc: 0.761437 [10] valid_0's auc: 0.763737 [11] valid_0's auc: 0.763776 [12] valid_0's auc: 0.763719 [13] valid_0's auc: 0.76376 [14] valid_0's auc: 0.765324 [15] valid_0's auc: 0.764771 [16] valid_0's auc: 0.765004 [17] valid_0's auc: 0.765143 [18] valid_0's auc: 0.765139 [19] valid_0's auc: 0.766475 [20] valid_0's auc: 0.766475 [21] valid_0's auc: 0.766487 [22] valid_0's auc: 0.766607 [23] valid_0's auc: 0.766948 [24] valid_0's auc: 0.766969 [25] valid_0's auc: 0.767293 [26] valid_0's auc: 0.76715 [27] valid_0's auc: 0.767735 [28] valid_0's auc: 0.767482 [29] valid_0's auc: 0.767415 [30] valid_0's auc: 0.767373 [31] valid_0's auc: 0.767466 [32] valid_0's auc: 0.767447 [33] valid_0's auc: 0.767597 [34] valid_0's auc: 0.767592 [35] valid_0's auc: 0.767583 [36] valid_0's auc: 0.767535 [37] valid_0's auc: 0.767569 [38] valid_0's auc: 0.767951 [39] valid_0's auc: 0.767957 [40] valid_0's auc: 0.767971 [41] valid_0's auc: 0.767935 [42] valid_0's auc: 0.772863 [43] valid_0's auc: 0.772794 [44] valid_0's auc: 0.772807 [45] valid_0's auc: 0.772689 [46] valid_0's auc: 0.773554 [47] valid_0's auc: 0.772882 [48] valid_0's auc: 0.773191 [49] valid_0's auc: 0.773343 [50] valid_0's auc: 0.773406 [51] valid_0's auc: 0.773419 [52] valid_0's auc: 0.773489 [53] valid_0's auc: 0.773811 [54] valid_0's auc: 0.774199 [55] valid_0's auc: 0.774412 [56] valid_0's auc: 0.774471 [57] valid_0's auc: 0.774837 [58] valid_0's auc: 0.774854 [59] valid_0's auc: 0.774845 [60] valid_0's auc: 0.775037 [61] valid_0's auc: 0.775005 [62] valid_0's auc: 0.775253 [63] valid_0's auc: 0.775098 [64] valid_0's auc: 0.775211 [65] valid_0's auc: 0.775622 [66] valid_0's auc: 0.775587 [67] valid_0's auc: 0.775568 [68] valid_0's auc: 0.775616 [69] valid_0's auc: 0.775411 [70] valid_0's auc: 0.776291 [71] valid_0's auc: 0.776298 [72] valid_0's auc: 0.776501 [73] valid_0's auc: 0.77645 [74] valid_0's auc: 0.776494 [75] valid_0's auc: 0.776403 [76] valid_0's auc: 0.775687 [77] valid_0's auc: 0.77577 [78] valid_0's auc: 0.776862 [79] valid_0's auc: 0.776278 [80] valid_0's auc: 0.777233 [81] valid_0's auc: 0.777851 [82] valid_0's auc: 0.778318 [83] valid_0's auc: 0.778309 [84] valid_0's auc: 0.778293 [85] valid_0's auc: 0.778611 [86] valid_0's auc: 0.778525 [87] valid_0's auc: 0.77854 [88] valid_0's auc: 0.778512 [89] valid_0's auc: 0.778519 [90] valid_0's auc: 0.778525 [91] valid_0's auc: 0.778497 [92] valid_0's auc: 0.778285 [93] valid_0's auc: 0.778654 [94] valid_0's auc: 0.77857 [95] valid_0's auc: 0.778521 [96] valid_0's auc: 0.778782 [97] valid_0's auc: 0.778835 [98] valid_0's auc: 0.779212 [99] valid_0's auc: 0.779191 [100] valid_0's auc: 0.779226 [1] valid_0's auc: 0.759786 [2] valid_0's auc: 0.764657 [3] valid_0's auc: 0.765416 [4] valid_0's auc: 0.765122 [5] valid_0's auc: 0.765122 [6] valid_0's auc: 0.76737 [7] valid_0's auc: 0.76737 [8] valid_0's auc: 0.768347 [9] valid_0's auc: 0.768542 [10] valid_0's auc: 0.769538 [11] valid_0's auc: 0.769651 [12] valid_0's auc: 0.769697 [13] valid_0's auc: 0.769702 [14] valid_0's auc: 0.769586 [15] valid_0's auc: 0.769466 [16] valid_0's auc: 0.769774 [17] valid_0's auc: 0.769894 [18] valid_0's auc: 0.769968 [19] valid_0's auc: 0.769984 [20] valid_0's auc: 0.769984 [21] valid_0's auc: 0.769921 [22] valid_0's auc: 0.770246 [23] valid_0's auc: 0.770348 [24] valid_0's auc: 0.770537 [25] valid_0's auc: 0.772107 [26] valid_0's auc: 0.772154 [27] valid_0's auc: 0.77229 [28] valid_0's auc: 0.772606 [29] valid_0's auc: 0.772221 [30] valid_0's auc: 0.77217 [31] valid_0's auc: 0.772283 [32] valid_0's auc: 0.772148 [33] valid_0's auc: 0.773711 [34] valid_0's auc: 0.773201 [35] valid_0's auc: 0.772608 [36] valid_0's auc: 0.773908 [37] valid_0's auc: 0.774534 [38] valid_0's auc: 0.774751 [39] valid_0's auc: 0.774889 [40] valid_0's auc: 0.776626 [41] valid_0's auc: 0.776385 [42] valid_0's auc: 0.776264 [43] valid_0's auc: 0.776878 [44] valid_0's auc: 0.777016 [45] valid_0's auc: 0.777825 [46] valid_0's auc: 0.778712 [47] valid_0's auc: 0.778604 [48] valid_0's auc: 0.778727 [49] valid_0's auc: 0.779104 [50] valid_0's auc: 0.779935 [51] valid_0's auc: 0.78035 [52] valid_0's auc: 0.781057 [53] valid_0's auc: 0.781113 [54] valid_0's auc: 0.781424 [55] valid_0's auc: 0.781814 [56] valid_0's auc: 0.781871 [57] valid_0's auc: 0.782098 [58] valid_0's auc: 0.782113 [59] valid_0's auc: 0.782133 [60] valid_0's auc: 0.782569 [61] valid_0's auc: 0.782645 [62] valid_0's auc: 0.782596 [63] valid_0's auc: 0.782709 [64] valid_0's auc: 0.782761 [65] valid_0's auc: 0.78289 [66] valid_0's auc: 0.782825 [67] valid_0's auc: 0.782821 [68] valid_0's auc: 0.782796 [69] valid_0's auc: 0.783017 [70] valid_0's auc: 0.783031 [71] valid_0's auc: 0.783049 [72] valid_0's auc: 0.783257 [73] valid_0's auc: 0.783257 [74] valid_0's auc: 0.783331 [75] valid_0's auc: 0.783258 [76] valid_0's auc: 0.783237 [77] valid_0's auc: 0.783262 [78] valid_0's auc: 0.783189 [79] valid_0's auc: 0.783448 [80] valid_0's auc: 0.783488 [81] valid_0's auc: 0.783661 [82] valid_0's auc: 0.783609 [83] valid_0's auc: 0.783617 [84] valid_0's auc: 0.783657 [85] valid_0's auc: 0.783607 [86] valid_0's auc: 0.783621 [87] valid_0's auc: 0.783634 [88] valid_0's auc: 0.783628 [89] valid_0's auc: 0.783654 [90] valid_0's auc: 0.783633 [91] valid_0's auc: 0.783581 [92] valid_0's auc: 0.783617 [93] valid_0's auc: 0.783681 [94] valid_0's auc: 0.783675 [95] valid_0's auc: 0.783676 [96] valid_0's auc: 0.783612 [97] valid_0's auc: 0.783626 [98] valid_0's auc: 0.783547 [99] valid_0's auc: 0.783576 [100] valid_0's auc: 0.783671 [1] valid_0's auc: 0.762215 [2] valid_0's auc: 0.772303 [3] valid_0's auc: 0.775269 [4] valid_0's auc: 0.774358 [5] valid_0's auc: 0.77429 [6] valid_0's auc: 0.77402 [7] valid_0's auc: 0.77402 [8] valid_0's auc: 0.775664 [9] valid_0's auc: 0.775678 [10] valid_0's auc: 0.775709 [11] valid_0's auc: 0.775825 [12] valid_0's auc: 0.775823 [13] valid_0's auc: 0.775947 [14] valid_0's auc: 0.777737 [15] valid_0's auc: 0.778991 [16] valid_0's auc: 0.778649 [17] valid_0's auc: 0.778267 [18] valid_0's auc: 0.778369 [19] valid_0's auc: 0.778369 [20] valid_0's auc: 0.778369 [21] valid_0's auc: 0.778406 [22] valid_0's auc: 0.778805 [23] valid_0's auc: 0.77886 [24] valid_0's auc: 0.778419 [25] valid_0's auc: 0.778975 [26] valid_0's auc: 0.779186 [27] valid_0's auc: 0.779731 [28] valid_0's auc: 0.780122 [29] valid_0's auc: 0.780195 [30] valid_0's auc: 0.780215 [31] valid_0's auc: 0.780063 [32] valid_0's auc: 0.780154 [33] valid_0's auc: 0.781266 [34] valid_0's auc: 0.781285 [35] valid_0's auc: 0.781159 [36] valid_0's auc: 0.781426 [37] valid_0's auc: 0.781279 [38] valid_0's auc: 0.781604 [39] valid_0's auc: 0.78167 [40] valid_0's auc: 0.781357 [41] valid_0's auc: 0.781469 [42] valid_0's auc: 0.781396 [43] valid_0's auc: 0.781686 [44] valid_0's auc: 0.781696 [45] valid_0's auc: 0.78168 [46] valid_0's auc: 0.781665 [47] valid_0's auc: 0.78171 [48] valid_0's auc: 0.781954 [49] valid_0's auc: 0.781862 [50] valid_0's auc: 0.781908 [51] valid_0's auc: 0.781837 [52] valid_0's auc: 0.781664 [53] valid_0's auc: 0.781803 [54] valid_0's auc: 0.781854 [55] valid_0's auc: 0.782152 [56] valid_0's auc: 0.783181 [57] valid_0's auc: 0.783197 [58] valid_0's auc: 0.783183 [59] valid_0's auc: 0.783246 [60] valid_0's auc: 0.78318 [61] valid_0's auc: 0.783197 [62] valid_0's auc: 0.783328 [63] valid_0's auc: 0.7834 [64] valid_0's auc: 0.78337 [65] valid_0's auc: 0.7834 [66] valid_0's auc: 0.783353 [67] valid_0's auc: 0.783377 [68] valid_0's auc: 0.783359 [69] valid_0's auc: 0.783296 [70] valid_0's auc: 0.78347 [71] valid_0's auc: 0.783464 [72] valid_0's auc: 0.783491 [73] valid_0's auc: 0.78345 [74] valid_0's auc: 0.783439 [75] valid_0's auc: 0.783415 [76] valid_0's auc: 0.783675 [77] valid_0's auc: 0.783755 [78] valid_0's auc: 0.783625 [79] valid_0's auc: 0.783749 [80] valid_0's auc: 0.783941 [81] valid_0's auc: 0.78379 [82] valid_0's auc: 0.784143 [83] valid_0's auc: 0.784113 [84] valid_0's auc: 0.784115 [85] valid_0's auc: 0.783958 [86] valid_0's auc: 0.784025 [87] valid_0's auc: 0.784022 [88] valid_0's auc: 0.784077 [89] valid_0's auc: 0.784074 [90] valid_0's auc: 0.784081 [91] valid_0's auc: 0.78425 [92] valid_0's auc: 0.784216 [93] valid_0's auc: 0.784472 [94] valid_0's auc: 0.784427 [95] valid_0's auc: 0.78431 [96] valid_0's auc: 0.784436 [97] valid_0's auc: 0.784476 [98] valid_0's auc: 0.784678 [99] valid_0's auc: 0.784664 [100] valid_0's auc: 0.784485 [1] valid_0's auc: 0.760477 [2] valid_0's auc: 0.760477 [3] valid_0's auc: 0.761049 [4] valid_0's auc: 0.762803 [5] valid_0's auc: 0.762803 [6] valid_0's auc: 0.764426 [7] valid_0's auc: 0.764426 [8] valid_0's auc: 0.763876 [9] valid_0's auc: 0.764608 [10] valid_0's auc: 0.764789 [11] valid_0's auc: 0.764761 [12] valid_0's auc: 0.764618 [13] valid_0's auc: 0.770857 [14] valid_0's auc: 0.770718 [15] valid_0's auc: 0.770783 [16] valid_0's auc: 0.771002 [17] valid_0's auc: 0.771467 [18] valid_0's auc: 0.771629 [19] valid_0's auc: 0.77172 [20] valid_0's auc: 0.77172 [21] valid_0's auc: 0.771722 [22] valid_0's auc: 0.771593 [23] valid_0's auc: 0.771624 [24] valid_0's auc: 0.771752 [25] valid_0's auc: 0.771876 [26] valid_0's auc: 0.772083 [27] valid_0's auc: 0.773213 [28] valid_0's auc: 0.773004 [29] valid_0's auc: 0.773093 [30] valid_0's auc: 0.772967 [31] valid_0's auc: 0.773117 [32] valid_0's auc: 0.773116 [33] valid_0's auc: 0.773506 [34] valid_0's auc: 0.773394 [35] valid_0's auc: 0.773326 [36] valid_0's auc: 0.773443 [37] valid_0's auc: 0.773701 [38] valid_0's auc: 0.77445 [39] valid_0's auc: 0.774493 [40] valid_0's auc: 0.774396 [41] valid_0's auc: 0.774179 [42] valid_0's auc: 0.774358 [43] valid_0's auc: 0.775014 [44] valid_0's auc: 0.774964 [45] valid_0's auc: 0.775465 [46] valid_0's auc: 0.776707 [47] valid_0's auc: 0.776664 [48] valid_0's auc: 0.776713 [49] valid_0's auc: 0.77668 [50] valid_0's auc: 0.777371 [51] valid_0's auc: 0.777236 [52] valid_0's auc: 0.77733 [53] valid_0's auc: 0.777753 [54] valid_0's auc: 0.777805 [55] valid_0's auc: 0.777714 [56] valid_0's auc: 0.778697 [57] valid_0's auc: 0.778794 [58] valid_0's auc: 0.778777 [59] valid_0's auc: 0.77882 [60] valid_0's auc: 0.779645 [61] valid_0's auc: 0.779869 [62] valid_0's auc: 0.779814 [63] valid_0's auc: 0.779875 [64] valid_0's auc: 0.779835 [65] valid_0's auc: 0.779921 [66] valid_0's auc: 0.779885 [67] valid_0's auc: 0.779928 [68] valid_0's auc: 0.779884 [69] valid_0's auc: 0.779864 [70] valid_0's auc: 0.779671 [71] valid_0's auc: 0.779628 [72] valid_0's auc: 0.7797 [73] valid_0's auc: 0.779669 [74] valid_0's auc: 0.779662 [75] valid_0's auc: 0.779602 [76] valid_0's auc: 0.779586 [77] valid_0's auc: 0.779785 [78] valid_0's auc: 0.779903 [79] valid_0's auc: 0.780292 [80] valid_0's auc: 0.780547 [81] valid_0's auc: 0.780595 [82] valid_0's auc: 0.780638 [83] valid_0's auc: 0.7806 [84] valid_0's auc: 0.78062 [85] valid_0's auc: 0.781164 [86] valid_0's auc: 0.78102 [87] valid_0's auc: 0.781019 [88] valid_0's auc: 0.781117 [89] valid_0's auc: 0.781135 [90] valid_0's auc: 0.78102 [91] valid_0's auc: 0.781003 [92] valid_0's auc: 0.780928 [93] valid_0's auc: 0.781373 [94] valid_0's auc: 0.781373 [95] valid_0's auc: 0.781288 [96] valid_0's auc: 0.781271 [97] valid_0's auc: 0.781279 [98] valid_0's auc: 0.781668 [99] valid_0's auc: 0.781582 [100] valid_0's auc: 0.781647 [1] valid_0's auc: 0.7495 [2] valid_0's auc: 0.7495 [3] valid_0's auc: 0.7495 [4] valid_0's auc: 0.751338 [5] valid_0's auc: 0.751338 [6] valid_0's auc: 0.750327 [7] valid_0's auc: 0.750327 [8] valid_0's auc: 0.750327 [9] valid_0's auc: 0.753589 [10] valid_0's auc: 0.751663 [11] valid_0's auc: 0.751663 [12] valid_0's auc: 0.751663 [13] valid_0's auc: 0.753629 [14] valid_0's auc: 0.751667 [15] valid_0's auc: 0.753799 [16] valid_0's auc: 0.75409 [17] valid_0's auc: 0.75437 [18] valid_0's auc: 0.754555 [19] valid_0's auc: 0.754555 [20] valid_0's auc: 0.75437 [21] valid_0's auc: 0.75454 [22] valid_0's auc: 0.754536 [23] valid_0's auc: 0.754532 [24] valid_0's auc: 0.754602 [25] valid_0's auc: 0.760514 [26] valid_0's auc: 0.760553 [27] valid_0's auc: 0.760625 [28] valid_0's auc: 0.76055 [29] valid_0's auc: 0.760601 [30] valid_0's auc: 0.760469 [31] valid_0's auc: 0.76243 [32] valid_0's auc: 0.762366 [33] valid_0's auc: 0.76231 [34] valid_0's auc: 0.762278 [35] valid_0's auc: 0.762393 [36] valid_0's auc: 0.762182 [37] valid_0's auc: 0.762012 [38] valid_0's auc: 0.762041 [39] valid_0's auc: 0.762299 [40] valid_0's auc: 0.762127 [41] valid_0's auc: 0.762302 [42] valid_0's auc: 0.762337 [43] valid_0's auc: 0.76231 [44] valid_0's auc: 0.762147 [45] valid_0's auc: 0.76238 [46] valid_0's auc: 0.762362 [47] valid_0's auc: 0.7624 [48] valid_0's auc: 0.762364 [49] valid_0's auc: 0.762933 [50] valid_0's auc: 0.763672 [51] valid_0's auc: 0.764058 [52] valid_0's auc: 0.764455 [53] valid_0's auc: 0.764269 [54] valid_0's auc: 0.766175 [55] valid_0's auc: 0.766913 [56] valid_0's auc: 0.767065 [57] valid_0's auc: 0.766834 [58] valid_0's auc: 0.766894 [59] valid_0's auc: 0.766915 [60] valid_0's auc: 0.766971 [61] valid_0's auc: 0.766952 [62] valid_0's auc: 0.767665 [63] valid_0's auc: 0.767655 [64] valid_0's auc: 0.767635 [65] valid_0's auc: 0.767597 [66] valid_0's auc: 0.767546 [67] valid_0's auc: 0.767567 [68] valid_0's auc: 0.76756 [69] valid_0's auc: 0.767479 [70] valid_0's auc: 0.767496 [71] valid_0's auc: 0.7675 [72] valid_0's auc: 0.767763 [73] valid_0's auc: 0.768087 [74] valid_0's auc: 0.76767 [75] valid_0's auc: 0.76772 [76] valid_0's auc: 0.767691 [77] valid_0's auc: 0.767619 [78] valid_0's auc: 0.767665 [79] valid_0's auc: 0.768263 [80] valid_0's auc: 0.768021 [81] valid_0's auc: 0.768156 [82] valid_0's auc: 0.769091 [83] valid_0's auc: 0.769085 [84] valid_0's auc: 0.769005 [85] valid_0's auc: 0.769298 [86] valid_0's auc: 0.769249 [87] valid_0's auc: 0.769219 [88] valid_0's auc: 0.769183 [89] valid_0's auc: 0.769129 [90] valid_0's auc: 0.769701 [91] valid_0's auc: 0.769705 [92] valid_0's auc: 0.769733 [93] valid_0's auc: 0.769842 [94] valid_0's auc: 0.769559 [95] valid_0's auc: 0.769506 [96] valid_0's auc: 0.769805 [97] valid_0's auc: 0.769775 [98] valid_0's auc: 0.769843 [99] valid_0's auc: 0.769828 [100] valid_0's auc: 0.769725 [1] valid_0's auc: 0.748453 [2] valid_0's auc: 0.750923 [3] valid_0's auc: 0.75159 [4] valid_0's auc: 0.752015 [5] valid_0's auc: 0.756456 [6] valid_0's auc: 0.757053 [7] valid_0's auc: 0.757053 [8] valid_0's auc: 0.757245 [9] valid_0's auc: 0.756643 [10] valid_0's auc: 0.756789 [11] valid_0's auc: 0.756791 [12] valid_0's auc: 0.757546 [13] valid_0's auc: 0.757041 [14] valid_0's auc: 0.757916 [15] valid_0's auc: 0.758323 [16] valid_0's auc: 0.762649 [17] valid_0's auc: 0.763888 [18] valid_0's auc: 0.763851 [19] valid_0's auc: 0.7643 [20] valid_0's auc: 0.7643 [21] valid_0's auc: 0.764526 [22] valid_0's auc: 0.765621 [23] valid_0's auc: 0.765736 [24] valid_0's auc: 0.765354 [25] valid_0's auc: 0.765948 [26] valid_0's auc: 0.765554 [27] valid_0's auc: 0.767708 [28] valid_0's auc: 0.768403 [29] valid_0's auc: 0.768837 [30] valid_0's auc: 0.767932 [31] valid_0's auc: 0.769135 [32] valid_0's auc: 0.768762 [33] valid_0's auc: 0.769205 [34] valid_0's auc: 0.769184 [35] valid_0's auc: 0.769103 [36] valid_0's auc: 0.769351 [37] valid_0's auc: 0.769706 [38] valid_0's auc: 0.770011 [39] valid_0's auc: 0.769793 [40] valid_0's auc: 0.769716 [41] valid_0's auc: 0.769734 [42] valid_0's auc: 0.769777 [43] valid_0's auc: 0.769948 [44] valid_0's auc: 0.769965 [45] valid_0's auc: 0.769943 [46] valid_0's auc: 0.770255 [47] valid_0's auc: 0.770166 [48] valid_0's auc: 0.770441 [49] valid_0's auc: 0.770272 [50] valid_0's auc: 0.77048 [51] valid_0's auc: 0.770307 [52] valid_0's auc: 0.77023 [53] valid_0's auc: 0.770333 [54] valid_0's auc: 0.770719 [55] valid_0's auc: 0.770651 [56] valid_0's auc: 0.770888 [57] valid_0's auc: 0.770661 [58] valid_0's auc: 0.770679 [59] valid_0's auc: 0.770734 [60] valid_0's auc: 0.770969 [61] valid_0's auc: 0.770957 [62] valid_0's auc: 0.770821 [63] valid_0's auc: 0.770921 [64] valid_0's auc: 0.77134 [65] valid_0's auc: 0.771506 [66] valid_0's auc: 0.771477 [67] valid_0's auc: 0.771467 [68] valid_0's auc: 0.771463 [69] valid_0's auc: 0.771513 [70] valid_0's auc: 0.771571 [71] valid_0's auc: 0.77151 [72] valid_0's auc: 0.77134 [73] valid_0's auc: 0.771352 [74] valid_0's auc: 0.771424 [75] valid_0's auc: 0.771336 [76] valid_0's auc: 0.771164 [77] valid_0's auc: 0.771425 [78] valid_0's auc: 0.771437 [79] valid_0's auc: 0.771328 [80] valid_0's auc: 0.771823 [81] valid_0's auc: 0.771911 [82] valid_0's auc: 0.771851 [83] valid_0's auc: 0.771943 [84] valid_0's auc: 0.77203 [85] valid_0's auc: 0.771763 [86] valid_0's auc: 0.771761 [87] valid_0's auc: 0.771757 [88] valid_0's auc: 0.771803 [89] valid_0's auc: 0.77181 [90] valid_0's auc: 0.771788 [91] valid_0's auc: 0.771799 [92] valid_0's auc: 0.771791 [93] valid_0's auc: 0.772506 [94] valid_0's auc: 0.772504 [95] valid_0's auc: 0.772567 [96] valid_0's auc: 0.7724 [97] valid_0's auc: 0.772422 [98] valid_0's auc: 0.772325 [99] valid_0's auc: 0.77207 [100] valid_0's auc: 0.772598 [1] valid_0's auc: 0.748867 [2] valid_0's auc: 0.764626 [3] valid_0's auc: 0.764062 [4] valid_0's auc: 0.763174 [5] valid_0's auc: 0.763174 [6] valid_0's auc: 0.762373 [7] valid_0's auc: 0.762373 [8] valid_0's auc: 0.762362 [9] valid_0's auc: 0.76208 [10] valid_0's auc: 0.764271 [11] valid_0's auc: 0.764385 [12] valid_0's auc: 0.764821 [13] valid_0's auc: 0.765442 [14] valid_0's auc: 0.765184 [15] valid_0's auc: 0.765028 [16] valid_0's auc: 0.764415 [17] valid_0's auc: 0.765623 [18] valid_0's auc: 0.766556 [19] valid_0's auc: 0.766645 [20] valid_0's auc: 0.766614 [21] valid_0's auc: 0.766746 [22] valid_0's auc: 0.7666 [23] valid_0's auc: 0.7666 [24] valid_0's auc: 0.76649 [25] valid_0's auc: 0.767107 [26] valid_0's auc: 0.767174 [27] valid_0's auc: 0.768623 [28] valid_0's auc: 0.768909 [29] valid_0's auc: 0.768838 [30] valid_0's auc: 0.768888 [31] valid_0's auc: 0.768729 [32] valid_0's auc: 0.768839 [33] valid_0's auc: 0.76912 [34] valid_0's auc: 0.769078 [35] valid_0's auc: 0.76903 [36] valid_0's auc: 0.768857 [37] valid_0's auc: 0.768625 [38] valid_0's auc: 0.769566 [39] valid_0's auc: 0.769595 [40] valid_0's auc: 0.769485 [41] valid_0's auc: 0.769462 [42] valid_0's auc: 0.769607 [43] valid_0's auc: 0.769984 [44] valid_0's auc: 0.77014 [45] valid_0's auc: 0.769858 [46] valid_0's auc: 0.770436 [47] valid_0's auc: 0.770434 [48] valid_0's auc: 0.770289 [49] valid_0's auc: 0.770654 [50] valid_0's auc: 0.769558 [51] valid_0's auc: 0.769724 [52] valid_0's auc: 0.769717 [53] valid_0's auc: 0.76963 [54] valid_0's auc: 0.770038 [55] valid_0's auc: 0.771136 [56] valid_0's auc: 0.771297 [57] valid_0's auc: 0.771245 [58] valid_0's auc: 0.771251 [59] valid_0's auc: 0.771149 [60] valid_0's auc: 0.77153 [61] valid_0's auc: 0.77158 [62] valid_0's auc: 0.771379 [63] valid_0's auc: 0.771845 [64] valid_0's auc: 0.771886 [65] valid_0's auc: 0.771767 [66] valid_0's auc: 0.77168 [67] valid_0's auc: 0.771708 [68] valid_0's auc: 0.771782 [69] valid_0's auc: 0.771657 [70] valid_0's auc: 0.771589 [71] valid_0's auc: 0.771596 [72] valid_0's auc: 0.771916 [73] valid_0's auc: 0.771913 [74] valid_0's auc: 0.771938 [75] valid_0's auc: 0.77189 [76] valid_0's auc: 0.771804 [77] valid_0's auc: 0.771921 [78] valid_0's auc: 0.772233 [79] valid_0's auc: 0.772134 [80] valid_0's auc: 0.772308 [81] valid_0's auc: 0.772456 [82] valid_0's auc: 0.772534 [83] valid_0's auc: 0.772563 [84] valid_0's auc: 0.77248 [85] valid_0's auc: 0.773027 [86] valid_0's auc: 0.773028 [87] valid_0's auc: 0.773038 [88] valid_0's auc: 0.773018 [89] valid_0's auc: 0.773081 [90] valid_0's auc: 0.773037 [91] valid_0's auc: 0.77304 [92] valid_0's auc: 0.773228 [93] valid_0's auc: 0.773083 [94] valid_0's auc: 0.77306 [95] valid_0's auc: 0.773082 [96] valid_0's auc: 0.773302 [97] valid_0's auc: 0.773207 [98] valid_0's auc: 0.773282 [99] valid_0's auc: 0.773215 [100] valid_0's auc: 0.773306 [1] valid_0's auc: 0.748286 [2] valid_0's auc: 0.748643 [3] valid_0's auc: 0.748974 [4] valid_0's auc: 0.749498 [5] valid_0's auc: 0.749498 [6] valid_0's auc: 0.7492 [7] valid_0's auc: 0.7492 [8] valid_0's auc: 0.752539 [9] valid_0's auc: 0.762203 [10] valid_0's auc: 0.762197 [11] valid_0's auc: 0.762188 [12] valid_0's auc: 0.762281 [13] valid_0's auc: 0.762658 [14] valid_0's auc: 0.762467 [15] valid_0's auc: 0.764294 [16] valid_0's auc: 0.765254 [17] valid_0's auc: 0.765911 [18] valid_0's auc: 0.765918 [19] valid_0's auc: 0.765884 [20] valid_0's auc: 0.765884 [21] valid_0's auc: 0.76579 [22] valid_0's auc: 0.765663 [23] valid_0's auc: 0.76566 [24] valid_0's auc: 0.765605 [25] valid_0's auc: 0.766181 [26] valid_0's auc: 0.766276 [27] valid_0's auc: 0.76655 [28] valid_0's auc: 0.766088 [29] valid_0's auc: 0.766655 [30] valid_0's auc: 0.766075 [31] valid_0's auc: 0.767689 [32] valid_0's auc: 0.767668 [33] valid_0's auc: 0.767533 [34] valid_0's auc: 0.767118 [35] valid_0's auc: 0.767054 [36] valid_0's auc: 0.766499 [37] valid_0's auc: 0.767457 [38] valid_0's auc: 0.767132 [39] valid_0's auc: 0.76716 [40] valid_0's auc: 0.767097 [41] valid_0's auc: 0.766949 [42] valid_0's auc: 0.76775 [43] valid_0's auc: 0.768144 [44] valid_0's auc: 0.768126 [45] valid_0's auc: 0.767837 [46] valid_0's auc: 0.768498 [47] valid_0's auc: 0.768361 [48] valid_0's auc: 0.768177 [49] valid_0's auc: 0.768134 [50] valid_0's auc: 0.768357 [51] valid_0's auc: 0.768274 [52] valid_0's auc: 0.768282 [53] valid_0's auc: 0.769519 [54] valid_0's auc: 0.769432 [55] valid_0's auc: 0.769116 [56] valid_0's auc: 0.769951 [57] valid_0's auc: 0.769814 [58] valid_0's auc: 0.769683 [59] valid_0's auc: 0.769728 [60] valid_0's auc: 0.769657 [61] valid_0's auc: 0.769657 [62] valid_0's auc: 0.770357 [63] valid_0's auc: 0.770351 [64] valid_0's auc: 0.770457 [65] valid_0's auc: 0.770513 [66] valid_0's auc: 0.770786 [67] valid_0's auc: 0.770685 [68] valid_0's auc: 0.770703 [69] valid_0's auc: 0.770468 [70] valid_0's auc: 0.770401 [71] valid_0's auc: 0.770392 [72] valid_0's auc: 0.770924 [73] valid_0's auc: 0.770897 [74] valid_0's auc: 0.770976 [75] valid_0's auc: 0.770904 [76] valid_0's auc: 0.770828 [77] valid_0's auc: 0.770694 [78] valid_0's auc: 0.771128 [79] valid_0's auc: 0.770851 [80] valid_0's auc: 0.770718 [81] valid_0's auc: 0.771544 [82] valid_0's auc: 0.771195 [83] valid_0's auc: 0.771197 [84] valid_0's auc: 0.771199 [85] valid_0's auc: 0.77162 [86] valid_0's auc: 0.771434 [87] valid_0's auc: 0.771354 [88] valid_0's auc: 0.771411 [89] valid_0's auc: 0.771386 [90] valid_0's auc: 0.771444 [91] valid_0's auc: 0.771538 [92] valid_0's auc: 0.771342 [93] valid_0's auc: 0.771303 [94] valid_0's auc: 0.771238 [95] valid_0's auc: 0.771726 [96] valid_0's auc: 0.771687 [97] valid_0's auc: 0.771616 [98] valid_0's auc: 0.771642 [99] valid_0's auc: 0.771567 [100] valid_0's auc: 0.771987 [1] valid_0's auc: 0.757043 [2] valid_0's auc: 0.757043 [3] valid_0's auc: 0.757043 [4] valid_0's auc: 0.757043 [5] valid_0's auc: 0.757043 [6] valid_0's auc: 0.757043 [7] valid_0's auc: 0.757043 [8] valid_0's auc: 0.757043 [9] valid_0's auc: 0.758795 [10] valid_0's auc: 0.760475 [11] valid_0's auc: 0.760597 [12] valid_0's auc: 0.760584 [13] valid_0's auc: 0.760681 [14] valid_0's auc: 0.760683 [15] valid_0's auc: 0.76056 [16] valid_0's auc: 0.761402 [17] valid_0's auc: 0.761529 [18] valid_0's auc: 0.761529 [19] valid_0's auc: 0.761591 [20] valid_0's auc: 0.761595 [21] valid_0's auc: 0.761558 [22] valid_0's auc: 0.761546 [23] valid_0's auc: 0.761522 [24] valid_0's auc: 0.761983 [25] valid_0's auc: 0.762505 [26] valid_0's auc: 0.762508 [27] valid_0's auc: 0.761965 [28] valid_0's auc: 0.762515 [29] valid_0's auc: 0.762438 [30] valid_0's auc: 0.761944 [31] valid_0's auc: 0.762352 [32] valid_0's auc: 0.762362 [33] valid_0's auc: 0.76204 [34] valid_0's auc: 0.762014 [35] valid_0's auc: 0.762034 [36] valid_0's auc: 0.762299 [37] valid_0's auc: 0.76202 [38] valid_0's auc: 0.762389 [39] valid_0's auc: 0.762389 [40] valid_0's auc: 0.76257 [41] valid_0's auc: 0.762487 [42] valid_0's auc: 0.768379 [43] valid_0's auc: 0.768593 [44] valid_0's auc: 0.768641 [45] valid_0's auc: 0.76864 [46] valid_0's auc: 0.768701 [47] valid_0's auc: 0.768685 [48] valid_0's auc: 0.768725 [49] valid_0's auc: 0.76878 [50] valid_0's auc: 0.768815 [51] valid_0's auc: 0.768899 [52] valid_0's auc: 0.769356 [53] valid_0's auc: 0.76957 [54] valid_0's auc: 0.769592 [55] valid_0's auc: 0.770163 [56] valid_0's auc: 0.770087 [57] valid_0's auc: 0.769987 [58] valid_0's auc: 0.770034 [59] valid_0's auc: 0.770034 [60] valid_0's auc: 0.770112 [61] valid_0's auc: 0.770101 [62] valid_0's auc: 0.77021 [63] valid_0's auc: 0.770568 [64] valid_0's auc: 0.770577 [65] valid_0's auc: 0.770507 [66] valid_0's auc: 0.770555 [67] valid_0's auc: 0.770527 [68] valid_0's auc: 0.770536 [69] valid_0's auc: 0.770528 [70] valid_0's auc: 0.770708 [71] valid_0's auc: 0.770806 [72] valid_0's auc: 0.770551 [73] valid_0's auc: 0.770486 [74] valid_0's auc: 0.770564 [75] valid_0's auc: 0.770553 [76] valid_0's auc: 0.770568 [77] valid_0's auc: 0.771518 [78] valid_0's auc: 0.772063 [79] valid_0's auc: 0.772278 [80] valid_0's auc: 0.772168 [81] valid_0's auc: 0.772335 [82] valid_0's auc: 0.772699 [83] valid_0's auc: 0.772683 [84] valid_0's auc: 0.772628 [85] valid_0's auc: 0.772676 [86] valid_0's auc: 0.772657 [87] valid_0's auc: 0.772683 [88] valid_0's auc: 0.772761 [89] valid_0's auc: 0.772677 [90] valid_0's auc: 0.772599 [91] valid_0's auc: 0.772597 [92] valid_0's auc: 0.772742 [93] valid_0's auc: 0.772798 [94] valid_0's auc: 0.772787 [95] valid_0's auc: 0.772724 [96] valid_0's auc: 0.773257 [97] valid_0's auc: 0.773116 [98] valid_0's auc: 0.773239 [99] valid_0's auc: 0.773173 [100] valid_0's auc: 0.772973 [1] valid_0's auc: 0.752298 [2] valid_0's auc: 0.759276 [3] valid_0's auc: 0.759067 [4] valid_0's auc: 0.760567 [5] valid_0's auc: 0.760567 [6] valid_0's auc: 0.759938 [7] valid_0's auc: 0.759938 [8] valid_0's auc: 0.760226 [9] valid_0's auc: 0.762248 [10] valid_0's auc: 0.76367 [11] valid_0's auc: 0.763621 [12] valid_0's auc: 0.763836 [13] valid_0's auc: 0.764138 [14] valid_0's auc: 0.763808 [15] valid_0's auc: 0.763779 [16] valid_0's auc: 0.764396 [17] valid_0's auc: 0.76465 [18] valid_0's auc: 0.764675 [19] valid_0's auc: 0.764672 [20] valid_0's auc: 0.764672 [21] valid_0's auc: 0.764679 [22] valid_0's auc: 0.764654 [23] valid_0's auc: 0.764654 [24] valid_0's auc: 0.764862 [25] valid_0's auc: 0.767665 [26] valid_0's auc: 0.767657 [27] valid_0's auc: 0.76752 [28] valid_0's auc: 0.768079 [29] valid_0's auc: 0.767723 [30] valid_0's auc: 0.767753 [31] valid_0's auc: 0.767904 [32] valid_0's auc: 0.767735 [33] valid_0's auc: 0.767987 [34] valid_0's auc: 0.767913 [35] valid_0's auc: 0.767958 [36] valid_0's auc: 0.767726 [37] valid_0's auc: 0.77144 [38] valid_0's auc: 0.771983 [39] valid_0's auc: 0.772072 [40] valid_0's auc: 0.772642 [41] valid_0's auc: 0.7724 [42] valid_0's auc: 0.772606 [43] valid_0's auc: 0.773112 [44] valid_0's auc: 0.773262 [45] valid_0's auc: 0.773283 [46] valid_0's auc: 0.7736 [47] valid_0's auc: 0.773597 [48] valid_0's auc: 0.774146 [49] valid_0's auc: 0.77475 [50] valid_0's auc: 0.775632 [51] valid_0's auc: 0.775868 [52] valid_0's auc: 0.776302 [53] valid_0's auc: 0.776677 [54] valid_0's auc: 0.776795 [55] valid_0's auc: 0.777018 [56] valid_0's auc: 0.776968 [57] valid_0's auc: 0.7774 [58] valid_0's auc: 0.77728 [59] valid_0's auc: 0.777279 [60] valid_0's auc: 0.777589 [61] valid_0's auc: 0.777624 [62] valid_0's auc: 0.777569 [63] valid_0's auc: 0.777958 [64] valid_0's auc: 0.778038 [65] valid_0's auc: 0.777877 [66] valid_0's auc: 0.777922 [67] valid_0's auc: 0.777913 [68] valid_0's auc: 0.777988 [69] valid_0's auc: 0.778129 [70] valid_0's auc: 0.778129 [71] valid_0's auc: 0.778101 [72] valid_0's auc: 0.778072 [73] valid_0's auc: 0.778109 [74] valid_0's auc: 0.778116 [75] valid_0's auc: 0.778077 [76] valid_0's auc: 0.778073 [77] valid_0's auc: 0.778366 [78] valid_0's auc: 0.778557 [79] valid_0's auc: 0.778774 [80] valid_0's auc: 0.778649 [81] valid_0's auc: 0.778791 [82] valid_0's auc: 0.779486 [83] valid_0's auc: 0.779434 [84] valid_0's auc: 0.779476 [85] valid_0's auc: 0.779434 [86] valid_0's auc: 0.779464 [87] valid_0's auc: 0.779465 [88] valid_0's auc: 0.779408 [89] valid_0's auc: 0.779419 [90] valid_0's auc: 0.779439 [91] valid_0's auc: 0.779496 [92] valid_0's auc: 0.779354 [93] valid_0's auc: 0.779674 [94] valid_0's auc: 0.779704 [95] valid_0's auc: 0.779594 [96] valid_0's auc: 0.779564 [97] valid_0's auc: 0.779641 [98] valid_0's auc: 0.779724 [99] valid_0's auc: 0.779738 [100] valid_0's auc: 0.779794 [1] valid_0's auc: 0.754636 [2] valid_0's auc: 0.768299 [3] valid_0's auc: 0.771575 [4] valid_0's auc: 0.770665 [5] valid_0's auc: 0.770665 [6] valid_0's auc: 0.772371 [7] valid_0's auc: 0.772371 [8] valid_0's auc: 0.772084 [9] valid_0's auc: 0.771631 [10] valid_0's auc: 0.771184 [11] valid_0's auc: 0.771361 [12] valid_0's auc: 0.771364 [13] valid_0's auc: 0.771236 [14] valid_0's auc: 0.77209 [15] valid_0's auc: 0.771527 [16] valid_0's auc: 0.773395 [17] valid_0's auc: 0.772813 [18] valid_0's auc: 0.772593 [19] valid_0's auc: 0.772593 [20] valid_0's auc: 0.772593 [21] valid_0's auc: 0.772756 [22] valid_0's auc: 0.772602 [23] valid_0's auc: 0.77261 [24] valid_0's auc: 0.772405 [25] valid_0's auc: 0.772337 [26] valid_0's auc: 0.773139 [27] valid_0's auc: 0.774044 [28] valid_0's auc: 0.774584 [29] valid_0's auc: 0.774653 [30] valid_0's auc: 0.774633 [31] valid_0's auc: 0.775546 [32] valid_0's auc: 0.775245 [33] valid_0's auc: 0.775 [34] valid_0's auc: 0.774977 [35] valid_0's auc: 0.774951 [36] valid_0's auc: 0.774779 [37] valid_0's auc: 0.774521 [38] valid_0's auc: 0.775045 [39] valid_0's auc: 0.775058 [40] valid_0's auc: 0.774883 [41] valid_0's auc: 0.774926 [42] valid_0's auc: 0.775126 [43] valid_0's auc: 0.775779 [44] valid_0's auc: 0.77582 [45] valid_0's auc: 0.775998 [46] valid_0's auc: 0.775977 [47] valid_0's auc: 0.775857 [48] valid_0's auc: 0.775963 [49] valid_0's auc: 0.77571 [50] valid_0's auc: 0.77598 [51] valid_0's auc: 0.776138 [52] valid_0's auc: 0.776229 [53] valid_0's auc: 0.776544 [54] valid_0's auc: 0.777067 [55] valid_0's auc: 0.776815 [56] valid_0's auc: 0.776867 [57] valid_0's auc: 0.777088 [58] valid_0's auc: 0.77714 [59] valid_0's auc: 0.777164 [60] valid_0's auc: 0.777809 [61] valid_0's auc: 0.777681 [62] valid_0's auc: 0.777586 [63] valid_0's auc: 0.777788 [64] valid_0's auc: 0.777767 [65] valid_0's auc: 0.778097 [66] valid_0's auc: 0.77814 [67] valid_0's auc: 0.778187 [68] valid_0's auc: 0.778159 [69] valid_0's auc: 0.778054 [70] valid_0's auc: 0.778241 [71] valid_0's auc: 0.778186 [72] valid_0's auc: 0.778181 [73] valid_0's auc: 0.778076 [74] valid_0's auc: 0.778134 [75] valid_0's auc: 0.778119 [76] valid_0's auc: 0.778214 [77] valid_0's auc: 0.778572 [78] valid_0's auc: 0.779137 [79] valid_0's auc: 0.778959 [80] valid_0's auc: 0.77866 [81] valid_0's auc: 0.779315 [82] valid_0's auc: 0.779205 [83] valid_0's auc: 0.77921 [84] valid_0's auc: 0.779256 [85] valid_0's auc: 0.778944 [86] valid_0's auc: 0.778859 [87] valid_0's auc: 0.77897 [88] valid_0's auc: 0.779201 [89] valid_0's auc: 0.779222 [90] valid_0's auc: 0.779197 [91] valid_0's auc: 0.779267 [92] valid_0's auc: 0.778952 [93] valid_0's auc: 0.778946 [94] valid_0's auc: 0.778927 [95] valid_0's auc: 0.779292 [96] valid_0's auc: 0.77937 [97] valid_0's auc: 0.779374 [98] valid_0's auc: 0.779003 [99] valid_0's auc: 0.779013 [100] valid_0's auc: 0.778886 [1] valid_0's auc: 0.757698 [2] valid_0's auc: 0.757948 [3] valid_0's auc: 0.758047 [4] valid_0's auc: 0.758753 [5] valid_0's auc: 0.758732 [6] valid_0's auc: 0.761583 [7] valid_0's auc: 0.761583 [8] valid_0's auc: 0.761034 [9] valid_0's auc: 0.762049 [10] valid_0's auc: 0.762074 [11] valid_0's auc: 0.762198 [12] valid_0's auc: 0.762199 [13] valid_0's auc: 0.767967 [14] valid_0's auc: 0.767981 [15] valid_0's auc: 0.767899 [16] valid_0's auc: 0.767954 [17] valid_0's auc: 0.769467 [18] valid_0's auc: 0.769501 [19] valid_0's auc: 0.769247 [20] valid_0's auc: 0.769247 [21] valid_0's auc: 0.769322 [22] valid_0's auc: 0.769347 [23] valid_0's auc: 0.769282 [24] valid_0's auc: 0.769233 [25] valid_0's auc: 0.769509 [26] valid_0's auc: 0.769618 [27] valid_0's auc: 0.770013 [28] valid_0's auc: 0.770055 [29] valid_0's auc: 0.770067 [30] valid_0's auc: 0.76999 [31] valid_0's auc: 0.770295 [32] valid_0's auc: 0.770246 [33] valid_0's auc: 0.770121 [34] valid_0's auc: 0.770037 [35] valid_0's auc: 0.770074 [36] valid_0's auc: 0.770297 [37] valid_0's auc: 0.77025 [38] valid_0's auc: 0.77052 [39] valid_0's auc: 0.770531 [40] valid_0's auc: 0.770241 [41] valid_0's auc: 0.770249 [42] valid_0's auc: 0.770513 [43] valid_0's auc: 0.771491 [44] valid_0's auc: 0.771462 [45] valid_0's auc: 0.771853 [46] valid_0's auc: 0.771821 [47] valid_0's auc: 0.771835 [48] valid_0's auc: 0.772956 [49] valid_0's auc: 0.772811 [50] valid_0's auc: 0.772768 [51] valid_0's auc: 0.773013 [52] valid_0's auc: 0.773168 [53] valid_0's auc: 0.772969 [54] valid_0's auc: 0.773559 [55] valid_0's auc: 0.773395 [56] valid_0's auc: 0.773962 [57] valid_0's auc: 0.773393 [58] valid_0's auc: 0.773411 [59] valid_0's auc: 0.773418 [60] valid_0's auc: 0.773612 [61] valid_0's auc: 0.773587 [62] valid_0's auc: 0.774549 [63] valid_0's auc: 0.775026 [64] valid_0's auc: 0.775062 [65] valid_0's auc: 0.775142 [66] valid_0's auc: 0.775147 [67] valid_0's auc: 0.775173 [68] valid_0's auc: 0.775176 [69] valid_0's auc: 0.774918 [70] valid_0's auc: 0.775034 [71] valid_0's auc: 0.77502 [72] valid_0's auc: 0.775638 [73] valid_0's auc: 0.775681 [74] valid_0's auc: 0.775659 [75] valid_0's auc: 0.775646 [76] valid_0's auc: 0.775464 [77] valid_0's auc: 0.775468 [78] valid_0's auc: 0.776185 [79] valid_0's auc: 0.776177 [80] valid_0's auc: 0.776149 [81] valid_0's auc: 0.776095 [82] valid_0's auc: 0.77591 [83] valid_0's auc: 0.77598 [84] valid_0's auc: 0.77593 [85] valid_0's auc: 0.776513 [86] valid_0's auc: 0.776489 [87] valid_0's auc: 0.776508 [88] valid_0's auc: 0.776496 [89] valid_0's auc: 0.776483 [90] valid_0's auc: 0.776364 [91] valid_0's auc: 0.776394 [92] valid_0's auc: 0.776189 [93] valid_0's auc: 0.776245 [94] valid_0's auc: 0.776325 [95] valid_0's auc: 0.776434 [96] valid_0's auc: 0.776475 [97] valid_0's auc: 0.776512 [98] valid_0's auc: 0.776745 [99] valid_0's auc: 0.776682 [100] valid_0's auc: 0.776691 [1] valid_0's auc: 0.760154 [2] valid_0's auc: 0.760161 [3] valid_0's auc: 0.761275 [4] valid_0's auc: 0.761194 [5] valid_0's auc: 0.761194 [6] valid_0's auc: 0.761366 [7] valid_0's auc: 0.761366 [8] valid_0's auc: 0.761278 [9] valid_0's auc: 0.761437 [10] valid_0's auc: 0.763737 [11] valid_0's auc: 0.763776 [12] valid_0's auc: 0.763719 [13] valid_0's auc: 0.76376 [14] valid_0's auc: 0.765324 [15] valid_0's auc: 0.764771 [16] valid_0's auc: 0.765004 [17] valid_0's auc: 0.765143 [18] valid_0's auc: 0.765139 [19] valid_0's auc: 0.766475 [20] valid_0's auc: 0.766475 [21] valid_0's auc: 0.766487 [22] valid_0's auc: 0.766607 [23] valid_0's auc: 0.766948 [24] valid_0's auc: 0.766969 [25] valid_0's auc: 0.767293 [26] valid_0's auc: 0.76715 [27] valid_0's auc: 0.767735 [28] valid_0's auc: 0.767482 [29] valid_0's auc: 0.767415 [30] valid_0's auc: 0.767373 [31] valid_0's auc: 0.767466 [32] valid_0's auc: 0.767447 [33] valid_0's auc: 0.767597 [34] valid_0's auc: 0.767592 [35] valid_0's auc: 0.767583 [36] valid_0's auc: 0.767535 [37] valid_0's auc: 0.767569 [38] valid_0's auc: 0.767951 [39] valid_0's auc: 0.767957 [40] valid_0's auc: 0.767971 [41] valid_0's auc: 0.767935 [42] valid_0's auc: 0.772863 [43] valid_0's auc: 0.772794 [44] valid_0's auc: 0.772807 [45] valid_0's auc: 0.772689 [46] valid_0's auc: 0.773554 [47] valid_0's auc: 0.772882 [48] valid_0's auc: 0.773191 [49] valid_0's auc: 0.773343 [50] valid_0's auc: 0.773406 [51] valid_0's auc: 0.773419 [52] valid_0's auc: 0.773489 [53] valid_0's auc: 0.773811 [54] valid_0's auc: 0.774199 [55] valid_0's auc: 0.774412 [56] valid_0's auc: 0.774471 [57] valid_0's auc: 0.774837 [58] valid_0's auc: 0.774854 [59] valid_0's auc: 0.774845 [60] valid_0's auc: 0.775037 [61] valid_0's auc: 0.775005 [62] valid_0's auc: 0.775253 [63] valid_0's auc: 0.775098 [64] valid_0's auc: 0.775211 [65] valid_0's auc: 0.775622 [66] valid_0's auc: 0.775587 [67] valid_0's auc: 0.775568 [68] valid_0's auc: 0.775616 [69] valid_0's auc: 0.775411 [70] valid_0's auc: 0.776291 [71] valid_0's auc: 0.776298 [72] valid_0's auc: 0.776501 [73] valid_0's auc: 0.77645 [74] valid_0's auc: 0.776494 [75] valid_0's auc: 0.776403 [76] valid_0's auc: 0.775687 [77] valid_0's auc: 0.77577 [78] valid_0's auc: 0.776862 [79] valid_0's auc: 0.776278 [80] valid_0's auc: 0.777233 [81] valid_0's auc: 0.777851 [82] valid_0's auc: 0.778318 [83] valid_0's auc: 0.778309 [84] valid_0's auc: 0.778293 [85] valid_0's auc: 0.778611 [86] valid_0's auc: 0.778525 [87] valid_0's auc: 0.77854 [88] valid_0's auc: 0.778512 [89] valid_0's auc: 0.778519 [90] valid_0's auc: 0.778525 [91] valid_0's auc: 0.778497 [92] valid_0's auc: 0.778285 [93] valid_0's auc: 0.778654 [94] valid_0's auc: 0.77857 [95] valid_0's auc: 0.778521 [96] valid_0's auc: 0.778782 [97] valid_0's auc: 0.778835 [98] valid_0's auc: 0.779212 [99] valid_0's auc: 0.779191 [100] valid_0's auc: 0.779226 [1] valid_0's auc: 0.759786 [2] valid_0's auc: 0.764657 [3] valid_0's auc: 0.765416 [4] valid_0's auc: 0.765122 [5] valid_0's auc: 0.765122 [6] valid_0's auc: 0.76737 [7] valid_0's auc: 0.76737 [8] valid_0's auc: 0.768347 [9] valid_0's auc: 0.768542 [10] valid_0's auc: 0.769538 [11] valid_0's auc: 0.769651 [12] valid_0's auc: 0.769697 [13] valid_0's auc: 0.769702 [14] valid_0's auc: 0.769586 [15] valid_0's auc: 0.769466 [16] valid_0's auc: 0.769774 [17] valid_0's auc: 0.769894 [18] valid_0's auc: 0.769968 [19] valid_0's auc: 0.769984 [20] valid_0's auc: 0.769984 [21] valid_0's auc: 0.769921 [22] valid_0's auc: 0.770246 [23] valid_0's auc: 0.770348 [24] valid_0's auc: 0.770537 [25] valid_0's auc: 0.772107 [26] valid_0's auc: 0.772154 [27] valid_0's auc: 0.77229 [28] valid_0's auc: 0.772606 [29] valid_0's auc: 0.772221 [30] valid_0's auc: 0.77217 [31] valid_0's auc: 0.772283 [32] valid_0's auc: 0.772148 [33] valid_0's auc: 0.773711 [34] valid_0's auc: 0.773201 [35] valid_0's auc: 0.772608 [36] valid_0's auc: 0.773908 [37] valid_0's auc: 0.774534 [38] valid_0's auc: 0.774751 [39] valid_0's auc: 0.774889 [40] valid_0's auc: 0.776626 [41] valid_0's auc: 0.776385 [42] valid_0's auc: 0.776264 [43] valid_0's auc: 0.776878 [44] valid_0's auc: 0.777016 [45] valid_0's auc: 0.777825 [46] valid_0's auc: 0.778712 [47] valid_0's auc: 0.778604 [48] valid_0's auc: 0.778727 [49] valid_0's auc: 0.779104 [50] valid_0's auc: 0.779935 [51] valid_0's auc: 0.78035 [52] valid_0's auc: 0.781057 [53] valid_0's auc: 0.781113 [54] valid_0's auc: 0.781424 [55] valid_0's auc: 0.781814 [56] valid_0's auc: 0.781871 [57] valid_0's auc: 0.782098 [58] valid_0's auc: 0.782113 [59] valid_0's auc: 0.782133 [60] valid_0's auc: 0.782569 [61] valid_0's auc: 0.782645 [62] valid_0's auc: 0.782596 [63] valid_0's auc: 0.782709 [64] valid_0's auc: 0.782761 [65] valid_0's auc: 0.78289 [66] valid_0's auc: 0.782825 [67] valid_0's auc: 0.782821 [68] valid_0's auc: 0.782796 [69] valid_0's auc: 0.783017 [70] valid_0's auc: 0.783031 [71] valid_0's auc: 0.783049 [72] valid_0's auc: 0.783257 [73] valid_0's auc: 0.783257 [74] valid_0's auc: 0.783331 [75] valid_0's auc: 0.783258 [76] valid_0's auc: 0.783237 [77] valid_0's auc: 0.783262 [78] valid_0's auc: 0.783189 [79] valid_0's auc: 0.783448 [80] valid_0's auc: 0.783488 [81] valid_0's auc: 0.783661 [82] valid_0's auc: 0.783609 [83] valid_0's auc: 0.783617 [84] valid_0's auc: 0.783657 [85] valid_0's auc: 0.783607 [86] valid_0's auc: 0.783621 [87] valid_0's auc: 0.783634 [88] valid_0's auc: 0.783628 [89] valid_0's auc: 0.783654 [90] valid_0's auc: 0.783633 [91] valid_0's auc: 0.783581 [92] valid_0's auc: 0.783617 [93] valid_0's auc: 0.783681 [94] valid_0's auc: 0.783675 [95] valid_0's auc: 0.783676 [96] valid_0's auc: 0.783612 [97] valid_0's auc: 0.783626 [98] valid_0's auc: 0.783547 [99] valid_0's auc: 0.783576 [100] valid_0's auc: 0.783671 [1] valid_0's auc: 0.762215 [2] valid_0's auc: 0.772303 [3] valid_0's auc: 0.775269 [4] valid_0's auc: 0.774358 [5] valid_0's auc: 0.77429 [6] valid_0's auc: 0.77402 [7] valid_0's auc: 0.77402 [8] valid_0's auc: 0.775664 [9] valid_0's auc: 0.775678 [10] valid_0's auc: 0.775709 [11] valid_0's auc: 0.775825 [12] valid_0's auc: 0.775823 [13] valid_0's auc: 0.775947 [14] valid_0's auc: 0.777737 [15] valid_0's auc: 0.778991 [16] valid_0's auc: 0.778649 [17] valid_0's auc: 0.778267 [18] valid_0's auc: 0.778369 [19] valid_0's auc: 0.778369 [20] valid_0's auc: 0.778369 [21] valid_0's auc: 0.778406 [22] valid_0's auc: 0.778805 [23] valid_0's auc: 0.77886 [24] valid_0's auc: 0.778419 [25] valid_0's auc: 0.778975 [26] valid_0's auc: 0.779186 [27] valid_0's auc: 0.779731 [28] valid_0's auc: 0.780122 [29] valid_0's auc: 0.780195 [30] valid_0's auc: 0.780215 [31] valid_0's auc: 0.780063 [32] valid_0's auc: 0.780154 [33] valid_0's auc: 0.781266 [34] valid_0's auc: 0.781285 [35] valid_0's auc: 0.781159 [36] valid_0's auc: 0.781426 [37] valid_0's auc: 0.781279 [38] valid_0's auc: 0.781604 [39] valid_0's auc: 0.78167 [40] valid_0's auc: 0.781357 [41] valid_0's auc: 0.781469 [42] valid_0's auc: 0.781396 [43] valid_0's auc: 0.781686 [44] valid_0's auc: 0.781696 [45] valid_0's auc: 0.78168 [46] valid_0's auc: 0.781665 [47] valid_0's auc: 0.78171 [48] valid_0's auc: 0.781954 [49] valid_0's auc: 0.781862 [50] valid_0's auc: 0.781908 [51] valid_0's auc: 0.781837 [52] valid_0's auc: 0.781664 [53] valid_0's auc: 0.781803 [54] valid_0's auc: 0.781854 [55] valid_0's auc: 0.782152 [56] valid_0's auc: 0.783181 [57] valid_0's auc: 0.783197 [58] valid_0's auc: 0.783183 [59] valid_0's auc: 0.783246 [60] valid_0's auc: 0.78318 [61] valid_0's auc: 0.783197 [62] valid_0's auc: 0.783328 [63] valid_0's auc: 0.7834 [64] valid_0's auc: 0.78337 [65] valid_0's auc: 0.7834 [66] valid_0's auc: 0.783353 [67] valid_0's auc: 0.783377 [68] valid_0's auc: 0.783359 [69] valid_0's auc: 0.783296 [70] valid_0's auc: 0.78347 [71] valid_0's auc: 0.783464 [72] valid_0's auc: 0.783491 [73] valid_0's auc: 0.78345 [74] valid_0's auc: 0.783439 [75] valid_0's auc: 0.783415 [76] valid_0's auc: 0.783675 [77] valid_0's auc: 0.783755 [78] valid_0's auc: 0.783625 [79] valid_0's auc: 0.783749 [80] valid_0's auc: 0.783941 [81] valid_0's auc: 0.78379 [82] valid_0's auc: 0.784143 [83] valid_0's auc: 0.784113 [84] valid_0's auc: 0.784115 [85] valid_0's auc: 0.783958 [86] valid_0's auc: 0.784025 [87] valid_0's auc: 0.784022 [88] valid_0's auc: 0.784077 [89] valid_0's auc: 0.784074 [90] valid_0's auc: 0.784081 [91] valid_0's auc: 0.78425 [92] valid_0's auc: 0.784216 [93] valid_0's auc: 0.784472 [94] valid_0's auc: 0.784427 [95] valid_0's auc: 0.78431 [96] valid_0's auc: 0.784436 [97] valid_0's auc: 0.784476 [98] valid_0's auc: 0.784678 [99] valid_0's auc: 0.784664 [100] valid_0's auc: 0.784485 [1] valid_0's auc: 0.760477 [2] valid_0's auc: 0.760477 [3] valid_0's auc: 0.761049 [4] valid_0's auc: 0.762803 [5] valid_0's auc: 0.762803 [6] valid_0's auc: 0.764426 [7] valid_0's auc: 0.764426 [8] valid_0's auc: 0.763876 [9] valid_0's auc: 0.764608 [10] valid_0's auc: 0.764789 [11] valid_0's auc: 0.764761 [12] valid_0's auc: 0.764618 [13] valid_0's auc: 0.770857 [14] valid_0's auc: 0.770718 [15] valid_0's auc: 0.770783 [16] valid_0's auc: 0.771002 [17] valid_0's auc: 0.771467 [18] valid_0's auc: 0.771629 [19] valid_0's auc: 0.77172 [20] valid_0's auc: 0.77172 [21] valid_0's auc: 0.771722 [22] valid_0's auc: 0.771593 [23] valid_0's auc: 0.771624 [24] valid_0's auc: 0.771752 [25] valid_0's auc: 0.771876 [26] valid_0's auc: 0.772083 [27] valid_0's auc: 0.773213 [28] valid_0's auc: 0.773004 [29] valid_0's auc: 0.773093 [30] valid_0's auc: 0.772967 [31] valid_0's auc: 0.773117 [32] valid_0's auc: 0.773116 [33] valid_0's auc: 0.773506 [34] valid_0's auc: 0.773394 [35] valid_0's auc: 0.773326 [36] valid_0's auc: 0.773443 [37] valid_0's auc: 0.773701 [38] valid_0's auc: 0.77445 [39] valid_0's auc: 0.774493 [40] valid_0's auc: 0.774396 [41] valid_0's auc: 0.774179 [42] valid_0's auc: 0.774358 [43] valid_0's auc: 0.775014 [44] valid_0's auc: 0.774964 [45] valid_0's auc: 0.775465 [46] valid_0's auc: 0.776707 [47] valid_0's auc: 0.776664 [48] valid_0's auc: 0.776713 [49] valid_0's auc: 0.77668 [50] valid_0's auc: 0.777371 [51] valid_0's auc: 0.777236 [52] valid_0's auc: 0.77733 [53] valid_0's auc: 0.777753 [54] valid_0's auc: 0.777805 [55] valid_0's auc: 0.777714 [56] valid_0's auc: 0.778697 [57] valid_0's auc: 0.778794 [58] valid_0's auc: 0.778777 [59] valid_0's auc: 0.77882 [60] valid_0's auc: 0.779645 [61] valid_0's auc: 0.779869 [62] valid_0's auc: 0.779814 [63] valid_0's auc: 0.779875 [64] valid_0's auc: 0.779835 [65] valid_0's auc: 0.779921 [66] valid_0's auc: 0.779885 [67] valid_0's auc: 0.779928 [68] valid_0's auc: 0.779884 [69] valid_0's auc: 0.779864 [70] valid_0's auc: 0.779671 [71] valid_0's auc: 0.779628 [72] valid_0's auc: 0.7797 [73] valid_0's auc: 0.779669 [74] valid_0's auc: 0.779662 [75] valid_0's auc: 0.779602 [76] valid_0's auc: 0.779586 [77] valid_0's auc: 0.779785 [78] valid_0's auc: 0.779903 [79] valid_0's auc: 0.780292 [80] valid_0's auc: 0.780547 [81] valid_0's auc: 0.780595 [82] valid_0's auc: 0.780638 [83] valid_0's auc: 0.7806 [84] valid_0's auc: 0.78062 [85] valid_0's auc: 0.781164 [86] valid_0's auc: 0.78102 [87] valid_0's auc: 0.781019 [88] valid_0's auc: 0.781117 [89] valid_0's auc: 0.781135 [90] valid_0's auc: 0.78102 [91] valid_0's auc: 0.781003 [92] valid_0's auc: 0.780928 [93] valid_0's auc: 0.781373 [94] valid_0's auc: 0.781373 [95] valid_0's auc: 0.781288 [96] valid_0's auc: 0.781271 [97] valid_0's auc: 0.781279 [98] valid_0's auc: 0.781668 [99] valid_0's auc: 0.781582 [100] valid_0's auc: 0.781647 [1] valid_0's auc: 0.7495 [2] valid_0's auc: 0.7495 [3] valid_0's auc: 0.7495 [4] valid_0's auc: 0.7495 [5] valid_0's auc: 0.7495 [6] valid_0's auc: 0.7495 [7] valid_0's auc: 0.7495 [8] valid_0's auc: 0.7495 [9] valid_0's auc: 0.7495 [10] valid_0's auc: 0.7495 [11] valid_0's auc: 0.7495 [12] valid_0's auc: 0.7495 [13] valid_0's auc: 0.7495 [14] valid_0's auc: 0.7495 [15] valid_0's auc: 0.7495 [16] valid_0's auc: 0.7495 [17] valid_0's auc: 0.7495 [18] valid_0's auc: 0.7495 [19] valid_0's auc: 0.7495 [20] valid_0's auc: 0.7495 [21] valid_0's auc: 0.7495 [22] valid_0's auc: 0.7495 [23] valid_0's auc: 0.7495 [24] valid_0's auc: 0.7495 [25] valid_0's auc: 0.7495 [26] valid_0's auc: 0.7495 [27] valid_0's auc: 0.7495 [28] valid_0's auc: 0.7495 [29] valid_0's auc: 0.7495 [30] valid_0's auc: 0.7495 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valid_0's auc: 0.7495 [49] valid_0's auc: 0.7495 [50] valid_0's auc: 0.7495 [51] valid_0's auc: 0.7495 [52] valid_0's auc: 0.7495 [53] valid_0's auc: 0.7495 [54] valid_0's auc: 0.7495 [55] valid_0's auc: 0.7495 [56] valid_0's auc: 0.7495 [57] valid_0's auc: 0.7495 [58] valid_0's auc: 0.7495 [59] valid_0's auc: 0.7495 [60] valid_0's auc: 0.7495 [61] valid_0's auc: 0.7495 [62] valid_0's auc: 0.7495 [63] valid_0's auc: 0.7495 [64] valid_0's auc: 0.7495 [65] valid_0's auc: 0.7495 [66] valid_0's auc: 0.7495 [67] valid_0's auc: 0.7495 [68] valid_0's auc: 0.7495 [69] valid_0's auc: 0.7495 [70] valid_0's auc: 0.7495 [71] valid_0's auc: 0.7495 [72] valid_0's auc: 0.7495 [73] valid_0's auc: 0.7495 [74] valid_0's auc: 0.7495 [75] valid_0's auc: 0.7495 [76] valid_0's auc: 0.7495 [77] valid_0's auc: 0.7495 [78] valid_0's auc: 0.7495 [79] valid_0's auc: 0.7495 [80] valid_0's auc: 0.7495 [81] valid_0's auc: 0.7495 [82] valid_0's auc: 0.7495 [83] valid_0's auc: 0.7495 [84] valid_0's auc: 0.7495 [85] valid_0's auc: 0.7495 [86] valid_0's auc: 0.7495 [87] valid_0's auc: 0.7495 [88] valid_0's auc: 0.7495 [89] valid_0's auc: 0.7495 [90] valid_0's auc: 0.7495 [91] valid_0's auc: 0.7495 [92] valid_0's auc: 0.7495 [93] valid_0's auc: 0.7495 [94] valid_0's auc: 0.7495 [95] valid_0's auc: 0.7495 [96] valid_0's auc: 0.7495 [97] valid_0's auc: 0.7495 [98] valid_0's auc: 0.7495 [99] valid_0's auc: 0.7495 [100] valid_0's auc: 0.7495 [1] valid_0's auc: 0.748453 [2] valid_0's auc: 0.748453 [3] valid_0's auc: 0.748453 [4] valid_0's auc: 0.748453 [5] valid_0's auc: 0.748453 [6] valid_0's auc: 0.748453 [7] valid_0's auc: 0.748453 [8] valid_0's auc: 0.748453 [9] valid_0's auc: 0.748453 [10] valid_0's auc: 0.748453 [11] valid_0's auc: 0.748453 [12] valid_0's auc: 0.748453 [13] valid_0's auc: 0.748453 [14] valid_0's auc: 0.748453 [15] valid_0's auc: 0.748453 [16] valid_0's auc: 0.748453 [17] valid_0's auc: 0.748453 [18] valid_0's auc: 0.748453 [19] valid_0's auc: 0.748453 [20] valid_0's auc: 0.748453 [21] valid_0's auc: 0.748453 [22] valid_0's auc: 0.748453 [23] valid_0's auc: 0.748453 [24] valid_0's auc: 0.748453 [25] valid_0's auc: 0.748453 [26] valid_0's auc: 0.748453 [27] valid_0's auc: 0.748453 [28] valid_0's auc: 0.748453 [29] valid_0's auc: 0.748453 [30] valid_0's auc: 0.748453 [31] valid_0's auc: 0.748453 [32] valid_0's auc: 0.748453 [33] valid_0's auc: 0.748453 [34] valid_0's auc: 0.748453 [35] valid_0's auc: 0.748453 [36] valid_0's auc: 0.748453 [37] valid_0's auc: 0.748453 [38] valid_0's auc: 0.748453 [39] valid_0's auc: 0.748453 [40] valid_0's auc: 0.748453 [41] valid_0's auc: 0.748453 [42] valid_0's auc: 0.748453 [43] valid_0's auc: 0.748453 [44] valid_0's auc: 0.748453 [45] valid_0's auc: 0.748453 [46] valid_0's auc: 0.748453 [47] valid_0's auc: 0.748453 [48] valid_0's auc: 0.748453 [49] valid_0's auc: 0.748453 [50] valid_0's auc: 0.748453 [51] valid_0's auc: 0.748453 [52] valid_0's auc: 0.748453 [53] valid_0's auc: 0.748453 [54] valid_0's auc: 0.748453 [55] valid_0's auc: 0.748453 [56] valid_0's auc: 0.748453 [57] valid_0's auc: 0.748453 [58] valid_0's auc: 0.748453 [59] valid_0's auc: 0.748453 [60] valid_0's auc: 0.748453 [61] valid_0's auc: 0.748453 [62] valid_0's auc: 0.748453 [63] valid_0's auc: 0.748453 [64] valid_0's auc: 0.748453 [65] valid_0's auc: 0.748453 [66] valid_0's auc: 0.748453 [67] valid_0's auc: 0.748453 [68] valid_0's auc: 0.748453 [69] valid_0's auc: 0.748453 [70] valid_0's auc: 0.748453 [71] valid_0's auc: 0.748453 [72] valid_0's auc: 0.748453 [73] valid_0's auc: 0.748453 [74] valid_0's auc: 0.748453 [75] valid_0's auc: 0.748453 [76] valid_0's auc: 0.748453 [77] valid_0's auc: 0.748453 [78] valid_0's auc: 0.748453 [79] valid_0's auc: 0.748453 [80] valid_0's auc: 0.748453 [81] valid_0's auc: 0.748453 [82] valid_0's auc: 0.748453 [83] valid_0's auc: 0.748453 [84] valid_0's auc: 0.748453 [85] valid_0's auc: 0.748453 [86] valid_0's auc: 0.748453 [87] valid_0's auc: 0.748453 [88] valid_0's auc: 0.748453 [89] valid_0's auc: 0.748453 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auc: 0.748286 [29] valid_0's auc: 0.748286 [30] valid_0's auc: 0.748286 [31] valid_0's auc: 0.748286 [32] valid_0's auc: 0.748286 [33] valid_0's auc: 0.748286 [34] valid_0's auc: 0.748286 [35] valid_0's auc: 0.748286 [36] valid_0's auc: 0.748286 [37] valid_0's auc: 0.748286 [38] valid_0's auc: 0.748286 [39] valid_0's auc: 0.748286 [40] valid_0's auc: 0.748286 [41] valid_0's auc: 0.748286 [42] valid_0's auc: 0.748286 [43] valid_0's auc: 0.748286 [44] valid_0's auc: 0.748286 [45] valid_0's auc: 0.748286 [46] valid_0's auc: 0.748286 [47] valid_0's auc: 0.748286 [48] valid_0's auc: 0.748286 [49] valid_0's auc: 0.748286 [50] valid_0's auc: 0.748286 [51] valid_0's auc: 0.748286 [52] valid_0's auc: 0.748286 [53] valid_0's auc: 0.748286 [54] valid_0's auc: 0.748286 [55] valid_0's auc: 0.748286 [56] valid_0's auc: 0.748286 [57] valid_0's auc: 0.748286 [58] valid_0's auc: 0.748286 [59] valid_0's auc: 0.748286 [60] valid_0's auc: 0.748286 [61] valid_0's auc: 0.748286 [62] valid_0's auc: 0.748286 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valid_0's auc: 0.752298 [2] valid_0's auc: 0.752298 [3] valid_0's auc: 0.752298 [4] valid_0's auc: 0.752298 [5] valid_0's auc: 0.752298 [6] valid_0's auc: 0.752298 [7] valid_0's auc: 0.752298 [8] valid_0's auc: 0.752298 [9] valid_0's auc: 0.752298 [10] valid_0's auc: 0.752298 [11] valid_0's auc: 0.752298 [12] valid_0's auc: 0.752298 [13] valid_0's auc: 0.752298 [14] valid_0's auc: 0.752298 [15] valid_0's auc: 0.752298 [16] valid_0's auc: 0.752298 [17] valid_0's auc: 0.752298 [18] valid_0's auc: 0.752298 [19] valid_0's auc: 0.752298 [20] valid_0's auc: 0.752298 [21] valid_0's auc: 0.752298 [22] valid_0's auc: 0.752298 [23] valid_0's auc: 0.752298 [24] valid_0's auc: 0.752298 [25] valid_0's auc: 0.752298 [26] valid_0's auc: 0.752298 [27] valid_0's auc: 0.752298 [28] valid_0's auc: 0.752298 [29] valid_0's auc: 0.752298 [30] valid_0's auc: 0.752298 [31] valid_0's auc: 0.752298 [32] valid_0's auc: 0.752298 [33] valid_0's auc: 0.752298 [34] valid_0's auc: 0.752298 [35] valid_0's auc: 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valid_0's auc: 0.759786 [16] valid_0's auc: 0.759786 [17] valid_0's auc: 0.759786 [18] valid_0's auc: 0.759786 [19] valid_0's auc: 0.759786 [20] valid_0's auc: 0.759786 [21] valid_0's auc: 0.759786 [22] valid_0's auc: 0.759786 [23] valid_0's auc: 0.759786 [24] valid_0's auc: 0.759786 [25] valid_0's auc: 0.759786 [26] valid_0's auc: 0.759786 [27] valid_0's auc: 0.759786 [28] valid_0's auc: 0.759786 [29] valid_0's auc: 0.759786 [30] valid_0's auc: 0.759786 [31] valid_0's auc: 0.759786 [32] valid_0's auc: 0.759786 [33] valid_0's auc: 0.759786 [34] valid_0's auc: 0.759786 [35] valid_0's auc: 0.759786 [36] valid_0's auc: 0.759786 [37] valid_0's auc: 0.759786 [38] valid_0's auc: 0.759786 [39] valid_0's auc: 0.759786 [40] valid_0's auc: 0.75979 [41] valid_0's auc: 0.75979 [42] valid_0's auc: 0.75979 [43] valid_0's auc: 0.75979 [44] valid_0's auc: 0.75979 [45] valid_0's auc: 0.75979 [46] valid_0's auc: 0.75979 [47] valid_0's auc: 0.75979 [48] valid_0's auc: 0.75979 [49] valid_0's auc: 0.759833 [50] valid_0's auc: 0.759833 [51] valid_0's auc: 0.759833 [52] valid_0's auc: 0.759833 [53] valid_0's auc: 0.759833 [54] valid_0's auc: 0.759939 [55] valid_0's auc: 0.759939 [56] valid_0's auc: 0.759939 [57] valid_0's auc: 0.759939 [58] valid_0's auc: 0.759939 [59] valid_0's auc: 0.759939 [60] valid_0's auc: 0.759939 [61] valid_0's auc: 0.759939 [62] valid_0's auc: 0.759939 [63] valid_0's auc: 0.759939 [64] valid_0's auc: 0.759939 [65] valid_0's auc: 0.759939 [66] valid_0's auc: 0.759939 [67] valid_0's auc: 0.759939 [68] valid_0's auc: 0.759939 [69] valid_0's auc: 0.759939 [70] valid_0's auc: 0.759939 [71] valid_0's auc: 0.759939 [72] valid_0's auc: 0.759939 [73] valid_0's auc: 0.759939 [74] valid_0's auc: 0.759939 [75] valid_0's auc: 0.759939 [76] valid_0's auc: 0.759939 [77] valid_0's auc: 0.759939 [78] valid_0's auc: 0.759939 [79] valid_0's auc: 0.759939 [80] valid_0's auc: 0.759939 [81] valid_0's auc: 0.759939 [82] valid_0's auc: 0.759939 [83] valid_0's auc: 0.759939 [84] valid_0's auc: 0.759939 [85] valid_0's auc: 0.759939 [86] valid_0's auc: 0.759939 [87] valid_0's auc: 0.759939 [88] valid_0's auc: 0.759939 [89] valid_0's auc: 0.759939 [90] valid_0's auc: 0.759939 [91] valid_0's auc: 0.759939 [92] valid_0's auc: 0.759939 [93] valid_0's auc: 0.759939 [94] valid_0's auc: 0.759939 [95] valid_0's auc: 0.759939 [96] valid_0's auc: 0.759939 [97] valid_0's auc: 0.759939 [98] valid_0's auc: 0.759939 [99] valid_0's auc: 0.759939 [100] valid_0's auc: 0.759939 [1] valid_0's auc: 0.762215 [2] valid_0's auc: 0.762215 [3] valid_0's auc: 0.762215 [4] valid_0's auc: 0.762215 [5] valid_0's auc: 0.762215 [6] valid_0's auc: 0.762215 [7] valid_0's auc: 0.762215 [8] valid_0's auc: 0.762215 [9] valid_0's auc: 0.762215 [10] valid_0's auc: 0.762215 [11] valid_0's auc: 0.762215 [12] valid_0's auc: 0.762215 [13] valid_0's auc: 0.762215 [14] valid_0's auc: 0.762215 [15] valid_0's auc: 0.762215 [16] valid_0's auc: 0.762215 [17] valid_0's auc: 0.762215 [18] valid_0's auc: 0.762215 [19] valid_0's auc: 0.762215 [20] valid_0's auc: 0.762215 [21] valid_0's auc: 0.762215 [22] valid_0's auc: 0.762215 [23] valid_0's auc: 0.762215 [24] valid_0's auc: 0.762215 [25] valid_0's auc: 0.762215 [26] valid_0's auc: 0.762215 [27] valid_0's auc: 0.762215 [28] valid_0's auc: 0.762215 [29] valid_0's auc: 0.762215 [30] valid_0's auc: 0.762215 [31] valid_0's auc: 0.762215 [32] valid_0's auc: 0.762215 [33] valid_0's auc: 0.762215 [34] valid_0's auc: 0.762215 [35] valid_0's auc: 0.762215 [36] valid_0's auc: 0.762215 [37] valid_0's auc: 0.762215 [38] valid_0's auc: 0.762215 [39] valid_0's auc: 0.762215 [40] valid_0's auc: 0.762215 [41] valid_0's auc: 0.762215 [42] valid_0's auc: 0.762215 [43] valid_0's auc: 0.762215 [44] valid_0's auc: 0.762215 [45] valid_0's auc: 0.762215 [46] valid_0's auc: 0.762215 [47] valid_0's auc: 0.762215 [48] valid_0's auc: 0.762215 [49] valid_0's auc: 0.762215 [50] valid_0's auc: 0.762215 [51] valid_0's auc: 0.762215 [52] valid_0's auc: 0.762512 [53] valid_0's auc: 0.762512 [54] valid_0's auc: 0.762512 [55] valid_0's auc: 0.762512 [56] valid_0's auc: 0.762512 [57] valid_0's auc: 0.762512 [58] valid_0's auc: 0.762512 [59] valid_0's auc: 0.762512 [60] valid_0's auc: 0.762512 [61] valid_0's auc: 0.762512 [62] valid_0's auc: 0.762512 [63] valid_0's auc: 0.762512 [64] valid_0's auc: 0.762512 [65] valid_0's auc: 0.762512 [66] valid_0's auc: 0.762512 [67] valid_0's auc: 0.762512 [68] valid_0's auc: 0.762512 [69] valid_0's auc: 0.762512 [70] valid_0's auc: 0.762512 [71] valid_0's auc: 0.762512 [72] valid_0's auc: 0.762512 [73] valid_0's auc: 0.762512 [74] valid_0's auc: 0.762512 [75] valid_0's auc: 0.762512 [76] valid_0's auc: 0.762512 [77] valid_0's auc: 0.762512 [78] valid_0's auc: 0.762512 [79] valid_0's auc: 0.762512 [80] valid_0's auc: 0.762562 [81] valid_0's auc: 0.762562 [82] valid_0's auc: 0.76264 [83] valid_0's auc: 0.76264 [84] valid_0's auc: 0.76264 [85] valid_0's auc: 0.76264 [86] valid_0's auc: 0.76264 [87] valid_0's auc: 0.76264 [88] valid_0's auc: 0.76264 [89] valid_0's auc: 0.76264 [90] valid_0's auc: 0.76264 [91] valid_0's auc: 0.76264 [92] valid_0's auc: 0.76264 [93] valid_0's auc: 0.76264 [94] valid_0's auc: 0.76264 [95] valid_0's auc: 0.762562 [96] valid_0's auc: 0.76264 [97] valid_0's auc: 0.76264 [98] valid_0's auc: 0.76264 [99] valid_0's auc: 0.76264 [100] valid_0's auc: 0.76264 [1] valid_0's auc: 0.760477 [2] valid_0's auc: 0.760477 [3] valid_0's auc: 0.760477 [4] valid_0's auc: 0.760477 [5] valid_0's auc: 0.760477 [6] valid_0's auc: 0.760477 [7] valid_0's auc: 0.760477 [8] valid_0's auc: 0.760477 [9] valid_0's auc: 0.760477 [10] valid_0's auc: 0.760477 [11] valid_0's auc: 0.760477 [12] valid_0's auc: 0.760477 [13] valid_0's auc: 0.760477 [14] valid_0's auc: 0.760477 [15] valid_0's auc: 0.760477 [16] valid_0's auc: 0.760477 [17] valid_0's auc: 0.760477 [18] valid_0's auc: 0.760477 [19] valid_0's auc: 0.760477 [20] valid_0's auc: 0.760477 [21] valid_0's auc: 0.760477 [22] valid_0's auc: 0.760477 [23] valid_0's auc: 0.760477 [24] valid_0's auc: 0.760477 [25] valid_0's auc: 0.760477 [26] valid_0's auc: 0.760477 [27] valid_0's auc: 0.760477 [28] valid_0's auc: 0.760477 [29] valid_0's auc: 0.760477 [30] valid_0's auc: 0.760477 [31] valid_0's auc: 0.760477 [32] valid_0's auc: 0.760477 [33] valid_0's auc: 0.760477 [34] valid_0's auc: 0.760477 [35] valid_0's auc: 0.760477 [36] valid_0's auc: 0.760477 [37] valid_0's auc: 0.760477 [38] valid_0's auc: 0.760477 [39] valid_0's auc: 0.760477 [40] valid_0's auc: 0.760477 [41] valid_0's auc: 0.760477 [42] valid_0's auc: 0.760477 [43] valid_0's auc: 0.760477 [44] valid_0's auc: 0.760477 [45] valid_0's auc: 0.760477 [46] valid_0's auc: 0.760477 [47] valid_0's auc: 0.760477 [48] valid_0's auc: 0.760477 [49] valid_0's auc: 0.760477 [50] valid_0's auc: 0.760477 [51] valid_0's auc: 0.760477 [52] valid_0's auc: 0.760477 [53] valid_0's auc: 0.760477 [54] valid_0's auc: 0.760477 [55] valid_0's auc: 0.760477 [56] valid_0's auc: 0.760477 [57] valid_0's auc: 0.760477 [58] valid_0's auc: 0.760477 [59] valid_0's auc: 0.760477 [60] valid_0's auc: 0.760477 [61] valid_0's auc: 0.760477 [62] valid_0's auc: 0.760477 [63] valid_0's auc: 0.760477 [64] valid_0's auc: 0.760477 [65] valid_0's auc: 0.760477 [66] valid_0's auc: 0.760477 [67] valid_0's auc: 0.760477 [68] valid_0's auc: 0.760477 [69] valid_0's auc: 0.760477 [70] valid_0's auc: 0.760477 [71] valid_0's auc: 0.760477 [72] valid_0's auc: 0.760477 [73] valid_0's auc: 0.760477 [74] valid_0's auc: 0.760477 [75] valid_0's auc: 0.760477 [76] valid_0's auc: 0.760477 [77] valid_0's auc: 0.760477 [78] valid_0's auc: 0.760477 [79] valid_0's auc: 0.760477 [80] valid_0's auc: 0.760477 [81] valid_0's auc: 0.760477 [82] valid_0's auc: 0.760477 [83] valid_0's auc: 0.760477 [84] valid_0's auc: 0.760477 [85] valid_0's auc: 0.760477 [86] valid_0's auc: 0.760477 [87] valid_0's auc: 0.760477 [88] valid_0's auc: 0.760477 [89] valid_0's auc: 0.760477 [90] valid_0's auc: 0.760477 [91] valid_0's auc: 0.760477 [92] valid_0's auc: 0.760477 [93] valid_0's auc: 0.760477 [94] valid_0's auc: 0.760477 [95] valid_0's auc: 0.760477 [96] valid_0's auc: 0.760477 [97] valid_0's auc: 0.760477 [98] valid_0's auc: 0.760477 [99] valid_0's auc: 0.760477 [100] valid_0's auc: 0.760477 [1] valid_0's auc: 0.7495 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.7495 [3] valid_0's auc: 0.7495 [4] valid_0's auc: 0.7495 [5] valid_0's auc: 0.7495 [6] valid_0's auc: 0.751338 [7] valid_0's auc: 0.751338 [8] valid_0's auc: 0.749299 [9] valid_0's auc: 0.750152 [10] valid_0's auc: 0.750327 [11] valid_0's auc: 0.753588 [12] valid_0's auc: 0.751726 [13] valid_0's auc: 0.753588 [14] valid_0's auc: 0.75362 [15] valid_0's auc: 0.752114 [16] valid_0's auc: 0.75397 [17] valid_0's auc: 0.752302 [18] valid_0's auc: 0.75454 [19] valid_0's auc: 0.754551 [20] valid_0's auc: 0.755186 [21] valid_0's auc: 0.755188 [22] valid_0's auc: 0.756006 [23] valid_0's auc: 0.75601 [24] valid_0's auc: 0.75633 [25] valid_0's auc: 0.756265 [26] valid_0's auc: 0.756053 [27] valid_0's auc: 0.756274 [28] valid_0's auc: 0.75762 [29] valid_0's auc: 0.756782 [30] valid_0's auc: 0.757634 [31] valid_0's auc: 0.757675 [32] valid_0's auc: 0.758008 [33] valid_0's auc: 0.756743 [34] valid_0's auc: 0.756602 [35] valid_0's auc: 0.757746 [36] valid_0's auc: 0.757017 [37] valid_0's auc: 0.757261 [38] valid_0's auc: 0.758645 [39] valid_0's auc: 0.758549 [40] valid_0's auc: 0.758784 [41] valid_0's auc: 0.758708 [42] valid_0's auc: 0.758747 [43] valid_0's auc: 0.758709 [44] valid_0's auc: 0.758743 [45] valid_0's auc: 0.759398 [46] valid_0's auc: 0.759397 [47] valid_0's auc: 0.759717 [48] valid_0's auc: 0.759915 [49] valid_0's auc: 0.759838 [50] valid_0's auc: 0.759863 [51] valid_0's auc: 0.76599 [52] valid_0's auc: 0.766056 [53] valid_0's auc: 0.766283 [54] valid_0's auc: 0.766718 [55] valid_0's auc: 0.766806 [56] valid_0's auc: 0.766793 [57] valid_0's auc: 0.766794 [58] valid_0's auc: 0.767103 [59] valid_0's auc: 0.76718 [60] valid_0's auc: 0.767451 [61] valid_0's auc: 0.767644 [62] valid_0's auc: 0.76792 [63] valid_0's auc: 0.768226 [64] valid_0's auc: 0.768386 [65] valid_0's auc: 0.768722 [66] valid_0's auc: 0.769498 [67] valid_0's auc: 0.769579 [68] valid_0's auc: 0.769717 [69] valid_0's auc: 0.769656 [70] valid_0's auc: 0.769725 [71] valid_0's auc: 0.770004 [72] valid_0's auc: 0.770071 [73] valid_0's auc: 0.770156 [74] valid_0's auc: 0.770421 [75] valid_0's auc: 0.770445 [76] valid_0's auc: 0.770643 [77] valid_0's auc: 0.770704 [78] valid_0's auc: 0.770812 [79] valid_0's auc: 0.771044 [80] valid_0's auc: 0.771391 [81] valid_0's auc: 0.771437 [82] valid_0's auc: 0.771472 [83] valid_0's auc: 0.771566 [84] valid_0's auc: 0.771689 [85] valid_0's auc: 0.771736 [86] valid_0's auc: 0.771801 [87] valid_0's auc: 0.772011 [88] valid_0's auc: 0.772728 [89] valid_0's auc: 0.7728 [90] valid_0's auc: 0.772898 [91] valid_0's auc: 0.772956 [92] valid_0's auc: 0.773111 [93] valid_0's auc: 0.773019 [94] valid_0's auc: 0.773114 [95] valid_0's auc: 0.773192 [96] valid_0's auc: 0.773362 [97] valid_0's auc: 0.77347 [98] valid_0's auc: 0.773557 [99] valid_0's auc: 0.773817 [100] valid_0's auc: 0.773901 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.773901 [1] valid_0's auc: 0.748453 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.749691 [3] valid_0's auc: 0.751615 [4] valid_0's auc: 0.751094 [5] valid_0's auc: 0.752006 [6] valid_0's auc: 0.751589 [7] valid_0's auc: 0.756645 [8] valid_0's auc: 0.756098 [9] valid_0's auc: 0.756598 [10] valid_0's auc: 0.756621 [11] valid_0's auc: 0.756363 [12] valid_0's auc: 0.756692 [13] valid_0's auc: 0.756926 [14] valid_0's auc: 0.757646 [15] valid_0's auc: 0.75773 [16] valid_0's auc: 0.761756 [17] valid_0's auc: 0.763676 [18] valid_0's auc: 0.763493 [19] valid_0's auc: 0.765036 [20] valid_0's auc: 0.765387 [21] valid_0's auc: 0.765743 [22] valid_0's auc: 0.76701 [23] valid_0's auc: 0.768299 [24] valid_0's auc: 0.768336 [25] valid_0's auc: 0.768381 [26] valid_0's auc: 0.768425 [27] valid_0's auc: 0.768594 [28] valid_0's auc: 0.768752 [29] valid_0's auc: 0.76916 [30] valid_0's auc: 0.769535 [31] valid_0's auc: 0.769674 [32] valid_0's auc: 0.76973 [33] valid_0's auc: 0.76982 [34] valid_0's auc: 0.769762 [35] valid_0's auc: 0.769653 [36] valid_0's auc: 0.769753 [37] valid_0's auc: 0.769828 [38] valid_0's auc: 0.769715 [39] valid_0's auc: 0.769539 [40] valid_0's auc: 0.769506 [41] valid_0's auc: 0.769693 [42] valid_0's auc: 0.769792 [43] valid_0's auc: 0.769553 [44] valid_0's auc: 0.769513 [45] valid_0's auc: 0.769447 [46] valid_0's auc: 0.770235 [47] valid_0's auc: 0.770256 [48] valid_0's auc: 0.770406 [49] valid_0's auc: 0.770384 [50] valid_0's auc: 0.770514 [51] valid_0's auc: 0.770421 [52] valid_0's auc: 0.770347 [53] valid_0's auc: 0.770589 [54] valid_0's auc: 0.770489 [55] valid_0's auc: 0.770481 [56] valid_0's auc: 0.770342 [57] valid_0's auc: 0.770254 [58] valid_0's auc: 0.770084 [59] valid_0's auc: 0.770734 [60] valid_0's auc: 0.770675 [61] valid_0's auc: 0.77066 [62] valid_0's auc: 0.770407 [63] valid_0's auc: 0.770372 [64] valid_0's auc: 0.770708 [65] valid_0's auc: 0.770528 [66] valid_0's auc: 0.770437 [67] valid_0's auc: 0.770418 [68] valid_0's auc: 0.77043 [69] valid_0's auc: 0.770575 Early stopping, best iteration is: [59] valid_0's auc: 0.770734 [1] valid_0's auc: 0.748867 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.762521 [3] valid_0's auc: 0.764062 [4] valid_0's auc: 0.763258 [5] valid_0's auc: 0.762373 [6] valid_0's auc: 0.764062 [7] valid_0's auc: 0.763748 [8] valid_0's auc: 0.763192 [9] valid_0's auc: 0.762451 [10] valid_0's auc: 0.762405 [11] valid_0's auc: 0.762414 [12] valid_0's auc: 0.762585 [13] valid_0's auc: 0.764478 [14] valid_0's auc: 0.763795 [15] valid_0's auc: 0.763768 [16] valid_0's auc: 0.765035 [17] valid_0's auc: 0.764958 [18] valid_0's auc: 0.764806 [19] valid_0's auc: 0.76476 [20] valid_0's auc: 0.764852 [21] valid_0's auc: 0.765044 [22] valid_0's auc: 0.765812 [23] valid_0's auc: 0.766688 [24] valid_0's auc: 0.766439 [25] valid_0's auc: 0.766191 [26] valid_0's auc: 0.765874 [27] valid_0's auc: 0.766426 [28] valid_0's auc: 0.766262 [29] valid_0's auc: 0.767146 [30] valid_0's auc: 0.767198 [31] valid_0's auc: 0.767499 [32] valid_0's auc: 0.767265 [33] valid_0's auc: 0.767585 [34] valid_0's auc: 0.767686 [35] valid_0's auc: 0.767393 [36] valid_0's auc: 0.76741 [37] valid_0's auc: 0.767271 [38] valid_0's auc: 0.767502 [39] valid_0's auc: 0.767493 [40] valid_0's auc: 0.768043 [41] valid_0's auc: 0.768017 [42] valid_0's auc: 0.767905 [43] valid_0's auc: 0.768008 [44] valid_0's auc: 0.767984 [45] valid_0's auc: 0.76836 [46] valid_0's auc: 0.768179 [47] valid_0's auc: 0.768016 [48] valid_0's auc: 0.768079 [49] valid_0's auc: 0.768291 [50] valid_0's auc: 0.768727 [51] valid_0's auc: 0.768816 [52] valid_0's auc: 0.768913 [53] valid_0's auc: 0.769575 [54] valid_0's auc: 0.769459 [55] valid_0's auc: 0.769078 [56] valid_0's auc: 0.769225 [57] valid_0's auc: 0.769868 [58] valid_0's auc: 0.769948 [59] valid_0's auc: 0.770082 [60] valid_0's auc: 0.770177 [61] valid_0's auc: 0.770308 [62] valid_0's auc: 0.770811 [63] valid_0's auc: 0.771087 [64] valid_0's auc: 0.771062 [65] valid_0's auc: 0.771391 [66] valid_0's auc: 0.771491 [67] valid_0's auc: 0.771609 [68] valid_0's auc: 0.771634 [69] valid_0's auc: 0.771639 [70] valid_0's auc: 0.77184 [71] valid_0's auc: 0.772131 [72] valid_0's auc: 0.772183 [73] valid_0's auc: 0.772289 [74] valid_0's auc: 0.772651 [75] valid_0's auc: 0.772794 [76] valid_0's auc: 0.772885 [77] valid_0's auc: 0.77315 [78] valid_0's auc: 0.773337 [79] valid_0's auc: 0.773271 [80] valid_0's auc: 0.77366 [81] valid_0's auc: 0.773411 [82] valid_0's auc: 0.773837 [83] valid_0's auc: 0.773812 [84] valid_0's auc: 0.774001 [85] valid_0's auc: 0.774302 [86] valid_0's auc: 0.774236 [87] valid_0's auc: 0.774115 [88] valid_0's auc: 0.77435 [89] valid_0's auc: 0.774409 [90] valid_0's auc: 0.774726 [91] valid_0's auc: 0.774635 [92] valid_0's auc: 0.774694 [93] valid_0's auc: 0.774737 [94] valid_0's auc: 0.774803 [95] valid_0's auc: 0.775202 [96] valid_0's auc: 0.775197 [97] valid_0's auc: 0.775361 [98] valid_0's auc: 0.775361 [99] valid_0's auc: 0.775321 [100] valid_0's auc: 0.775437 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.775437 [1] valid_0's auc: 0.748286 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.748286 [3] valid_0's auc: 0.749259 [4] valid_0's auc: 0.749362 [5] valid_0's auc: 0.748976 [6] valid_0's auc: 0.74936 [7] valid_0's auc: 0.749362 [8] valid_0's auc: 0.749138 [9] valid_0's auc: 0.752684 [10] valid_0's auc: 0.752831 [11] valid_0's auc: 0.75366 [12] valid_0's auc: 0.75411 [13] valid_0's auc: 0.761886 [14] valid_0's auc: 0.762058 [15] valid_0's auc: 0.761342 [16] valid_0's auc: 0.762343 [17] valid_0's auc: 0.763406 [18] valid_0's auc: 0.763392 [19] valid_0's auc: 0.763273 [20] valid_0's auc: 0.76458 [21] valid_0's auc: 0.763966 [22] valid_0's auc: 0.764795 [23] valid_0's auc: 0.765132 [24] valid_0's auc: 0.765137 [25] valid_0's auc: 0.765224 [26] valid_0's auc: 0.765178 [27] valid_0's auc: 0.765203 [28] valid_0's auc: 0.765275 [29] valid_0's auc: 0.76528 [30] valid_0's auc: 0.765251 [31] valid_0's auc: 0.766388 [32] valid_0's auc: 0.76663 [33] valid_0's auc: 0.766285 [34] valid_0's auc: 0.766925 [35] valid_0's auc: 0.766744 [36] valid_0's auc: 0.766676 [37] valid_0's auc: 0.767472 [38] valid_0's auc: 0.76736 [39] valid_0's auc: 0.767359 [40] valid_0's auc: 0.76739 [41] valid_0's auc: 0.767703 [42] valid_0's auc: 0.767477 [43] valid_0's auc: 0.767541 [44] valid_0's auc: 0.767863 [45] valid_0's auc: 0.767699 [46] valid_0's auc: 0.767717 [47] valid_0's auc: 0.76795 [48] valid_0's auc: 0.767933 [49] valid_0's auc: 0.767932 [50] valid_0's auc: 0.768455 [51] valid_0's auc: 0.768476 [52] valid_0's auc: 0.76847 [53] valid_0's auc: 0.76849 [54] valid_0's auc: 0.768749 [55] valid_0's auc: 0.768557 [56] valid_0's auc: 0.769161 [57] valid_0's auc: 0.769234 [58] valid_0's auc: 0.769464 [59] valid_0's auc: 0.769393 [60] valid_0's auc: 0.769274 [61] valid_0's auc: 0.769263 [62] valid_0's auc: 0.769402 [63] valid_0's auc: 0.769438 [64] valid_0's auc: 0.76958 [65] valid_0's auc: 0.769563 [66] valid_0's auc: 0.769568 [67] valid_0's auc: 0.769779 [68] valid_0's auc: 0.769926 [69] valid_0's auc: 0.769944 [70] valid_0's auc: 0.770306 [71] valid_0's auc: 0.770275 [72] valid_0's auc: 0.770372 [73] valid_0's auc: 0.771305 [74] valid_0's auc: 0.771477 [75] valid_0's auc: 0.771405 [76] valid_0's auc: 0.771388 [77] valid_0's auc: 0.771519 [78] valid_0's auc: 0.771588 [79] valid_0's auc: 0.772025 [80] valid_0's auc: 0.772217 [81] valid_0's auc: 0.772321 [82] valid_0's auc: 0.772388 [83] valid_0's auc: 0.772701 [84] valid_0's auc: 0.772712 [85] valid_0's auc: 0.772697 [86] valid_0's auc: 0.773027 [87] valid_0's auc: 0.773182 [88] valid_0's auc: 0.773352 [89] valid_0's auc: 0.773592 [90] valid_0's auc: 0.773594 [91] valid_0's auc: 0.773858 [92] valid_0's auc: 0.773981 [93] valid_0's auc: 0.774091 [94] valid_0's auc: 0.77409 [95] valid_0's auc: 0.774341 [96] valid_0's auc: 0.774392 [97] valid_0's auc: 0.774483 [98] valid_0's auc: 0.774577 [99] valid_0's auc: 0.774593 [100] valid_0's auc: 0.774762 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.774762 [1] valid_0's auc: 0.757043 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.757043 [3] valid_0's auc: 0.757043 [4] valid_0's auc: 0.757043 [5] valid_0's auc: 0.757043 [6] valid_0's auc: 0.757043 [7] valid_0's auc: 0.757043 [8] valid_0's auc: 0.757043 [9] valid_0's auc: 0.757043 [10] valid_0's auc: 0.757043 [11] valid_0's auc: 0.758625 [12] valid_0's auc: 0.759292 [13] valid_0's auc: 0.760187 [14] valid_0's auc: 0.760275 [15] valid_0's auc: 0.760962 [16] valid_0's auc: 0.761238 [17] valid_0's auc: 0.761211 [18] valid_0's auc: 0.7613 [19] valid_0's auc: 0.761395 [20] valid_0's auc: 0.761334 [21] valid_0's auc: 0.761432 [22] valid_0's auc: 0.761521 [23] valid_0's auc: 0.761593 [24] valid_0's auc: 0.761667 [25] valid_0's auc: 0.761781 [26] valid_0's auc: 0.762145 [27] valid_0's auc: 0.762147 [28] valid_0's auc: 0.762012 [29] valid_0's auc: 0.762029 [30] valid_0's auc: 0.76205 [31] valid_0's auc: 0.7623 [32] valid_0's auc: 0.762442 [33] valid_0's auc: 0.762826 [34] valid_0's auc: 0.762886 [35] valid_0's auc: 0.762847 [36] valid_0's auc: 0.762868 [37] valid_0's auc: 0.762924 [38] valid_0's auc: 0.763281 [39] valid_0's auc: 0.76328 [40] valid_0's auc: 0.763148 [41] valid_0's auc: 0.763354 [42] valid_0's auc: 0.764574 [43] valid_0's auc: 0.764801 [44] valid_0's auc: 0.764879 [45] valid_0's auc: 0.765002 [46] valid_0's auc: 0.76495 [47] valid_0's auc: 0.765176 [48] valid_0's auc: 0.765224 [49] valid_0's auc: 0.76525 [50] valid_0's auc: 0.765488 [51] valid_0's auc: 0.765558 [52] valid_0's auc: 0.765553 [53] valid_0's auc: 0.765663 [54] valid_0's auc: 0.765647 [55] valid_0's auc: 0.766129 [56] valid_0's auc: 0.766111 [57] valid_0's auc: 0.765746 [58] valid_0's auc: 0.76651 [59] valid_0's auc: 0.766548 [60] valid_0's auc: 0.766745 [61] valid_0's auc: 0.771389 [62] valid_0's auc: 0.771551 [63] valid_0's auc: 0.771669 [64] valid_0's auc: 0.771897 [65] valid_0's auc: 0.771982 [66] valid_0's auc: 0.772083 [67] valid_0's auc: 0.772517 [68] valid_0's auc: 0.772629 [69] valid_0's auc: 0.773429 [70] valid_0's auc: 0.773844 [71] valid_0's auc: 0.773989 [72] valid_0's auc: 0.774098 [73] valid_0's auc: 0.775047 [74] valid_0's auc: 0.775309 [75] valid_0's auc: 0.775532 [76] valid_0's auc: 0.775546 [77] valid_0's auc: 0.77575 [78] valid_0's auc: 0.775891 [79] valid_0's auc: 0.776002 [80] valid_0's auc: 0.776212 [81] valid_0's auc: 0.776492 [82] valid_0's auc: 0.776616 [83] valid_0's auc: 0.776783 [84] valid_0's auc: 0.776891 [85] valid_0's auc: 0.776979 [86] valid_0's auc: 0.777022 [87] valid_0's auc: 0.777174 [88] valid_0's auc: 0.777333 [89] valid_0's auc: 0.77745 [90] valid_0's auc: 0.77752 [91] valid_0's auc: 0.777574 [92] valid_0's auc: 0.777644 [93] valid_0's auc: 0.777846 [94] valid_0's auc: 0.777805 [95] valid_0's auc: 0.777825 [96] valid_0's auc: 0.777932 [97] valid_0's auc: 0.778095 [98] valid_0's auc: 0.778152 [99] valid_0's auc: 0.778222 [100] valid_0's auc: 0.778231 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.778231 [1] valid_0's auc: 0.752298 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.759276 [3] valid_0's auc: 0.759067 [4] valid_0's auc: 0.759079 [5] valid_0's auc: 0.759532 [6] valid_0's auc: 0.759549 [7] valid_0's auc: 0.761225 [8] valid_0's auc: 0.761092 [9] valid_0's auc: 0.761531 [10] valid_0's auc: 0.761654 [11] valid_0's auc: 0.76183 [12] valid_0's auc: 0.761651 [13] valid_0's auc: 0.761898 [14] valid_0's auc: 0.763021 [15] valid_0's auc: 0.763917 [16] valid_0's auc: 0.764055 [17] valid_0's auc: 0.764371 [18] valid_0's auc: 0.764469 [19] valid_0's auc: 0.764181 [20] valid_0's auc: 0.764792 [21] valid_0's auc: 0.764872 [22] valid_0's auc: 0.766306 [23] valid_0's auc: 0.766454 [24] valid_0's auc: 0.766814 [25] valid_0's auc: 0.770826 [26] valid_0's auc: 0.77106 [27] valid_0's auc: 0.771193 [28] valid_0's auc: 0.771275 [29] valid_0's auc: 0.771764 [30] valid_0's auc: 0.772921 [31] valid_0's auc: 0.772755 [32] valid_0's auc: 0.772821 [33] valid_0's auc: 0.773079 [34] valid_0's auc: 0.774193 [35] valid_0's auc: 0.774257 [36] valid_0's auc: 0.774432 [37] valid_0's auc: 0.774706 [38] valid_0's auc: 0.775102 [39] valid_0's auc: 0.775298 [40] valid_0's auc: 0.775427 [41] valid_0's auc: 0.77582 [42] valid_0's auc: 0.775949 [43] valid_0's auc: 0.776069 [44] valid_0's auc: 0.776087 [45] valid_0's auc: 0.776161 [46] valid_0's auc: 0.776193 [47] valid_0's auc: 0.776459 [48] valid_0's auc: 0.776804 [49] valid_0's auc: 0.777155 [50] valid_0's auc: 0.777061 [51] valid_0's auc: 0.777348 [52] valid_0's auc: 0.777465 [53] valid_0's auc: 0.777494 [54] valid_0's auc: 0.777575 [55] valid_0's auc: 0.777784 [56] valid_0's auc: 0.777784 [57] valid_0's auc: 0.777785 [58] valid_0's auc: 0.77793 [59] valid_0's auc: 0.778083 [60] valid_0's auc: 0.778009 [61] valid_0's auc: 0.778058 [62] valid_0's auc: 0.778052 [63] valid_0's auc: 0.777929 [64] valid_0's auc: 0.778139 [65] valid_0's auc: 0.778281 [66] valid_0's auc: 0.778265 [67] valid_0's auc: 0.778265 [68] valid_0's auc: 0.77838 [69] valid_0's auc: 0.778393 [70] valid_0's auc: 0.778366 [71] valid_0's auc: 0.778427 [72] valid_0's auc: 0.778364 [73] valid_0's auc: 0.778342 [74] valid_0's auc: 0.778339 [75] valid_0's auc: 0.778291 [76] valid_0's auc: 0.778306 [77] valid_0's auc: 0.778345 [78] valid_0's auc: 0.778399 [79] valid_0's auc: 0.778372 [80] valid_0's auc: 0.778413 [81] valid_0's auc: 0.778537 [82] valid_0's auc: 0.77857 [83] valid_0's auc: 0.778721 [84] valid_0's auc: 0.778712 [85] valid_0's auc: 0.778755 [86] valid_0's auc: 0.778862 [87] valid_0's auc: 0.779 [88] valid_0's auc: 0.780026 [89] valid_0's auc: 0.780002 [90] valid_0's auc: 0.780006 [91] valid_0's auc: 0.780188 [92] valid_0's auc: 0.780227 [93] valid_0's auc: 0.780227 [94] valid_0's auc: 0.780421 [95] valid_0's auc: 0.780511 [96] valid_0's auc: 0.780642 [97] valid_0's auc: 0.780721 [98] valid_0's auc: 0.780743 [99] valid_0's auc: 0.780898 [100] valid_0's auc: 0.780924 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.780924 [1] valid_0's auc: 0.754636 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.7683 [3] valid_0's auc: 0.76755 [4] valid_0's auc: 0.771673 [5] valid_0's auc: 0.772091 [6] valid_0's auc: 0.771553 [7] valid_0's auc: 0.771367 [8] valid_0's auc: 0.770636 [9] valid_0's auc: 0.771707 [10] valid_0's auc: 0.771595 [11] valid_0's auc: 0.771764 [12] valid_0's auc: 0.771648 [13] valid_0's auc: 0.771187 [14] valid_0's auc: 0.77186 [15] valid_0's auc: 0.771543 Early stopping, best iteration is: [5] valid_0's auc: 0.772091 [1] valid_0's auc: 0.757698 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.757698 [3] valid_0's auc: 0.758663 [4] valid_0's auc: 0.757968 [5] valid_0's auc: 0.757959 [6] valid_0's auc: 0.757982 [7] valid_0's auc: 0.758325 [8] valid_0's auc: 0.758427 [9] valid_0's auc: 0.760477 [10] valid_0's auc: 0.761208 [11] valid_0's auc: 0.762052 [12] valid_0's auc: 0.762095 [13] valid_0's auc: 0.762074 [14] valid_0's auc: 0.762127 [15] valid_0's auc: 0.762133 [16] valid_0's auc: 0.762254 [17] valid_0's auc: 0.762284 [18] valid_0's auc: 0.761951 [19] valid_0's auc: 0.761953 [20] valid_0's auc: 0.762233 [21] valid_0's auc: 0.763617 [22] valid_0's auc: 0.763017 [23] valid_0's auc: 0.76413 [24] valid_0's auc: 0.764133 [25] valid_0's auc: 0.764182 [26] valid_0's auc: 0.764466 [27] valid_0's auc: 0.76447 [28] valid_0's auc: 0.764439 [29] valid_0's auc: 0.764552 [30] valid_0's auc: 0.764529 [31] valid_0's auc: 0.764645 [32] valid_0's auc: 0.76461 [33] valid_0's auc: 0.764749 [34] valid_0's auc: 0.764821 [35] valid_0's auc: 0.764874 [36] valid_0's auc: 0.765379 [37] valid_0's auc: 0.76569 [38] valid_0's auc: 0.771086 [39] valid_0's auc: 0.771052 [40] valid_0's auc: 0.770973 [41] valid_0's auc: 0.770923 [42] valid_0's auc: 0.771175 [43] valid_0's auc: 0.771435 [44] valid_0's auc: 0.771566 [45] valid_0's auc: 0.771553 [46] valid_0's auc: 0.77223 [47] valid_0's auc: 0.772217 [48] valid_0's auc: 0.772403 [49] valid_0's auc: 0.772724 [50] valid_0's auc: 0.772727 [51] valid_0's auc: 0.772736 [52] valid_0's auc: 0.772851 [53] valid_0's auc: 0.772891 [54] valid_0's auc: 0.773151 [55] valid_0's auc: 0.773219 [56] valid_0's auc: 0.773409 [57] valid_0's auc: 0.773384 [58] valid_0's auc: 0.773475 [59] valid_0's auc: 0.773402 [60] valid_0's auc: 0.773757 [61] valid_0's auc: 0.773803 [62] valid_0's auc: 0.774054 [63] valid_0's auc: 0.774023 [64] valid_0's auc: 0.774089 [65] valid_0's auc: 0.774476 [66] valid_0's auc: 0.774687 [67] valid_0's auc: 0.774747 [68] valid_0's auc: 0.774837 [69] valid_0's auc: 0.774838 [70] valid_0's auc: 0.775095 [71] valid_0's auc: 0.775076 [72] valid_0's auc: 0.775126 [73] valid_0's auc: 0.775658 [74] valid_0's auc: 0.775383 [75] valid_0's auc: 0.776725 [76] valid_0's auc: 0.776896 [77] valid_0's auc: 0.777285 [78] valid_0's auc: 0.777833 [79] valid_0's auc: 0.778284 [80] valid_0's auc: 0.778558 [81] valid_0's auc: 0.778694 [82] valid_0's auc: 0.778815 [83] valid_0's auc: 0.779367 [84] valid_0's auc: 0.779458 [85] valid_0's auc: 0.779447 [86] valid_0's auc: 0.779756 [87] valid_0's auc: 0.779789 [88] valid_0's auc: 0.779914 [89] valid_0's auc: 0.780055 [90] valid_0's auc: 0.780157 [91] valid_0's auc: 0.780275 [92] valid_0's auc: 0.780355 [93] valid_0's auc: 0.780553 [94] valid_0's auc: 0.78061 [95] valid_0's auc: 0.780827 [96] valid_0's auc: 0.780831 [97] valid_0's auc: 0.781015 [98] valid_0's auc: 0.781166 [99] valid_0's auc: 0.781131 [100] valid_0's auc: 0.781194 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.781194 [1] valid_0's auc: 0.760154 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.760161 [3] valid_0's auc: 0.760248 [4] valid_0's auc: 0.760916 [5] valid_0's auc: 0.761004 [6] valid_0's auc: 0.76127 [7] valid_0's auc: 0.7613 [8] valid_0's auc: 0.76127 [9] valid_0's auc: 0.761278 [10] valid_0's auc: 0.761278 [11] valid_0's auc: 0.761268 [12] valid_0's auc: 0.761437 [13] valid_0's auc: 0.76341 [14] valid_0's auc: 0.764528 [15] valid_0's auc: 0.764469 [16] valid_0's auc: 0.766352 [17] valid_0's auc: 0.767053 [18] valid_0's auc: 0.766859 [19] valid_0's auc: 0.767212 [20] valid_0's auc: 0.766872 [21] valid_0's auc: 0.766866 [22] valid_0's auc: 0.767423 [23] valid_0's auc: 0.767323 [24] valid_0's auc: 0.767413 [25] valid_0's auc: 0.767656 [26] valid_0's auc: 0.767654 [27] valid_0's auc: 0.767613 [28] valid_0's auc: 0.767717 [29] valid_0's auc: 0.768226 [30] valid_0's auc: 0.768494 [31] valid_0's auc: 0.768577 [32] valid_0's auc: 0.768808 [33] valid_0's auc: 0.768591 [34] valid_0's auc: 0.768697 [35] valid_0's auc: 0.769098 [36] valid_0's auc: 0.769009 [37] valid_0's auc: 0.769042 [38] valid_0's auc: 0.769575 [39] valid_0's auc: 0.76962 [40] valid_0's auc: 0.76958 [41] valid_0's auc: 0.769666 [42] valid_0's auc: 0.769771 [43] valid_0's auc: 0.769773 [44] valid_0's auc: 0.769946 [45] valid_0's auc: 0.769864 [46] valid_0's auc: 0.770008 [47] valid_0's auc: 0.770105 [48] valid_0's auc: 0.770358 [49] valid_0's auc: 0.770544 [50] valid_0's auc: 0.770754 [51] valid_0's auc: 0.770966 [52] valid_0's auc: 0.770991 [53] valid_0's auc: 0.770996 [54] valid_0's auc: 0.771023 [55] valid_0's auc: 0.771135 [56] valid_0's auc: 0.775167 [57] valid_0's auc: 0.775182 [58] valid_0's auc: 0.775229 [59] valid_0's auc: 0.775415 [60] valid_0's auc: 0.775413 [61] valid_0's auc: 0.775489 [62] valid_0's auc: 0.775545 [63] valid_0's auc: 0.775602 [64] valid_0's auc: 0.77607 [65] valid_0's auc: 0.776277 [66] valid_0's auc: 0.777002 [67] valid_0's auc: 0.7773 [68] valid_0's auc: 0.777466 [69] valid_0's auc: 0.778277 [70] valid_0's auc: 0.778481 [71] valid_0's auc: 0.779101 [72] valid_0's auc: 0.77928 [73] valid_0's auc: 0.779498 [74] valid_0's auc: 0.779962 [75] valid_0's auc: 0.780241 [76] valid_0's auc: 0.78028 [77] valid_0's auc: 0.78044 [78] valid_0's auc: 0.780489 [79] valid_0's auc: 0.780655 [80] valid_0's auc: 0.780801 [81] valid_0's auc: 0.780863 [82] valid_0's auc: 0.781056 [83] valid_0's auc: 0.781219 [84] valid_0's auc: 0.781239 [85] valid_0's auc: 0.781329 [86] valid_0's auc: 0.781488 [87] valid_0's auc: 0.781692 [88] valid_0's auc: 0.781652 [89] valid_0's auc: 0.78181 [90] valid_0's auc: 0.781885 [91] valid_0's auc: 0.782033 [92] valid_0's auc: 0.782059 [93] valid_0's auc: 0.782156 [94] valid_0's auc: 0.78235 [95] valid_0's auc: 0.782382 [96] valid_0's auc: 0.782505 [97] valid_0's auc: 0.782803 [98] valid_0's auc: 0.782928 [99] valid_0's auc: 0.782958 [100] valid_0's auc: 0.783127 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.783127 [1] valid_0's auc: 0.759786 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.764657 [3] valid_0's auc: 0.764758 [4] valid_0's auc: 0.764375 [5] valid_0's auc: 0.766985 [6] valid_0's auc: 0.767135 [7] valid_0's auc: 0.767228 [8] valid_0's auc: 0.767524 [9] valid_0's auc: 0.767575 [10] valid_0's auc: 0.768459 [11] valid_0's auc: 0.768472 [12] valid_0's auc: 0.768308 [13] valid_0's auc: 0.768742 [14] valid_0's auc: 0.76912 [15] valid_0's auc: 0.769523 [16] valid_0's auc: 0.769527 [17] valid_0's auc: 0.769747 [18] valid_0's auc: 0.770015 [19] valid_0's auc: 0.770021 [20] valid_0's auc: 0.770216 [21] valid_0's auc: 0.770394 [22] valid_0's auc: 0.770491 [23] valid_0's auc: 0.771372 [24] valid_0's auc: 0.77146 [25] valid_0's auc: 0.772478 [26] valid_0's auc: 0.774667 [27] valid_0's auc: 0.775156 [28] valid_0's auc: 0.775394 [29] valid_0's auc: 0.776522 [30] valid_0's auc: 0.777059 [31] valid_0's auc: 0.777769 [32] valid_0's auc: 0.778398 [33] valid_0's auc: 0.77855 [34] valid_0's auc: 0.778852 [35] valid_0's auc: 0.778991 [36] valid_0's auc: 0.779339 [37] valid_0's auc: 0.779584 [38] valid_0's auc: 0.779981 [39] valid_0's auc: 0.780291 [40] valid_0's auc: 0.780597 [41] valid_0's auc: 0.780625 [42] valid_0's auc: 0.781065 [43] valid_0's auc: 0.781104 [44] valid_0's auc: 0.78122 [45] valid_0's auc: 0.781282 [46] valid_0's auc: 0.781359 [47] valid_0's auc: 0.781428 [48] valid_0's auc: 0.781493 [49] valid_0's auc: 0.781566 [50] valid_0's auc: 0.781573 [51] valid_0's auc: 0.781657 [52] valid_0's auc: 0.781654 [53] valid_0's auc: 0.781991 [54] valid_0's auc: 0.781977 [55] valid_0's auc: 0.781937 [56] valid_0's auc: 0.782062 [57] valid_0's auc: 0.782204 [58] valid_0's auc: 0.782183 [59] valid_0's auc: 0.782284 [60] valid_0's auc: 0.78236 [61] valid_0's auc: 0.782299 [62] valid_0's auc: 0.782241 [63] valid_0's auc: 0.782255 [64] valid_0's auc: 0.782392 [65] valid_0's auc: 0.782954 [66] valid_0's auc: 0.783 [67] valid_0's auc: 0.783067 [68] valid_0's auc: 0.783055 [69] valid_0's auc: 0.783199 [70] valid_0's auc: 0.784276 [71] valid_0's auc: 0.784242 [72] valid_0's auc: 0.784126 [73] valid_0's auc: 0.784678 [74] valid_0's auc: 0.784838 [75] valid_0's auc: 0.784647 [76] valid_0's auc: 0.78471 [77] valid_0's auc: 0.785257 [78] valid_0's auc: 0.785353 [79] valid_0's auc: 0.785299 [80] valid_0's auc: 0.785447 [81] valid_0's auc: 0.785441 [82] valid_0's auc: 0.785337 [83] valid_0's auc: 0.785524 [84] valid_0's auc: 0.785471 [85] valid_0's auc: 0.785644 [86] valid_0's auc: 0.785397 [87] valid_0's auc: 0.785544 [88] valid_0's auc: 0.785513 [89] valid_0's auc: 0.785843 [90] valid_0's auc: 0.785886 [91] valid_0's auc: 0.786101 [92] valid_0's auc: 0.786287 [93] valid_0's auc: 0.786388 [94] valid_0's auc: 0.786446 [95] valid_0's auc: 0.786717 [96] valid_0's auc: 0.786801 [97] valid_0's auc: 0.786936 [98] valid_0's auc: 0.786962 [99] valid_0's auc: 0.787115 [100] valid_0's auc: 0.787182 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.787182 [1] valid_0's auc: 0.762215 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.772303 [3] valid_0's auc: 0.772421 [4] valid_0's auc: 0.776396 [5] valid_0's auc: 0.776041 [6] valid_0's auc: 0.775312 [7] valid_0's auc: 0.775295 [8] valid_0's auc: 0.774564 [9] valid_0's auc: 0.775867 [10] valid_0's auc: 0.776069 [11] valid_0's auc: 0.77626 [12] valid_0's auc: 0.775754 [13] valid_0's auc: 0.775736 [14] valid_0's auc: 0.775701 Early stopping, best iteration is: [4] valid_0's auc: 0.776396 [1] valid_0's auc: 0.760477 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.760477 [3] valid_0's auc: 0.760477 [4] valid_0's auc: 0.760477 [5] valid_0's auc: 0.761103 [6] valid_0's auc: 0.761047 [7] valid_0's auc: 0.761742 [8] valid_0's auc: 0.762091 [9] valid_0's auc: 0.761811 [10] valid_0's auc: 0.762913 [11] valid_0's auc: 0.764336 [12] valid_0's auc: 0.764575 [13] valid_0's auc: 0.76471 [14] valid_0's auc: 0.764793 [15] valid_0's auc: 0.764833 [16] valid_0's auc: 0.764858 [17] valid_0's auc: 0.765272 [18] valid_0's auc: 0.765434 [19] valid_0's auc: 0.765433 [20] valid_0's auc: 0.765377 [21] valid_0's auc: 0.766184 [22] valid_0's auc: 0.766292 [23] valid_0's auc: 0.766241 [24] valid_0's auc: 0.766845 [25] valid_0's auc: 0.766847 [26] valid_0's auc: 0.76682 [27] valid_0's auc: 0.766822 [28] valid_0's auc: 0.766843 [29] valid_0's auc: 0.767279 [30] valid_0's auc: 0.767148 [31] valid_0's auc: 0.771446 [32] valid_0's auc: 0.771758 [33] valid_0's auc: 0.772053 [34] valid_0's auc: 0.772218 [35] valid_0's auc: 0.77235 [36] valid_0's auc: 0.772422 [37] valid_0's auc: 0.772691 [38] valid_0's auc: 0.772759 [39] valid_0's auc: 0.77303 [40] valid_0's auc: 0.773159 [41] valid_0's auc: 0.773573 [42] valid_0's auc: 0.773811 [43] valid_0's auc: 0.774071 [44] valid_0's auc: 0.775543 [45] valid_0's auc: 0.775683 [46] valid_0's auc: 0.775777 [47] valid_0's auc: 0.776504 [48] valid_0's auc: 0.776461 [49] valid_0's auc: 0.776618 [50] valid_0's auc: 0.776668 [51] valid_0's auc: 0.776907 [52] valid_0's auc: 0.777106 [53] valid_0's auc: 0.777089 [54] valid_0's auc: 0.77738 [55] valid_0's auc: 0.777284 [56] valid_0's auc: 0.777854 [57] valid_0's auc: 0.777969 [58] valid_0's auc: 0.777917 [59] valid_0's auc: 0.77859 [60] valid_0's auc: 0.778583 [61] valid_0's auc: 0.778918 [62] valid_0's auc: 0.779783 [63] valid_0's auc: 0.779196 [64] valid_0's auc: 0.780008 [65] valid_0's auc: 0.780037 [66] valid_0's auc: 0.781486 [67] valid_0's auc: 0.781619 [68] valid_0's auc: 0.781764 [69] valid_0's auc: 0.781837 [70] valid_0's auc: 0.782085 [71] valid_0's auc: 0.782169 [72] valid_0's auc: 0.782249 [73] valid_0's auc: 0.782379 [74] valid_0's auc: 0.782491 [75] valid_0's auc: 0.782881 [76] valid_0's auc: 0.783108 [77] valid_0's auc: 0.783322 [78] valid_0's auc: 0.78374 [79] valid_0's auc: 0.783882 [80] valid_0's auc: 0.784251 [81] valid_0's auc: 0.784354 [82] valid_0's auc: 0.78441 [83] valid_0's auc: 0.784621 [84] valid_0's auc: 0.784695 [85] valid_0's auc: 0.784797 [86] valid_0's auc: 0.784856 [87] valid_0's auc: 0.785046 [88] valid_0's auc: 0.785056 [89] valid_0's auc: 0.785259 [90] valid_0's auc: 0.785669 [91] valid_0's auc: 0.785821 [92] valid_0's auc: 0.786026 [93] valid_0's auc: 0.786013 [94] valid_0's auc: 0.786032 [95] valid_0's auc: 0.786231 [96] valid_0's auc: 0.786296 [97] valid_0's auc: 0.78644 [98] valid_0's auc: 0.786566 [99] valid_0's auc: 0.786242 [100] valid_0's auc: 0.786363 Did not meet early stopping. Best iteration is: [98] valid_0's auc: 0.786566 [1] valid_0's auc: 0.7495 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.7495 [3] valid_0's auc: 0.7495 [4] valid_0's auc: 0.7495 [5] valid_0's auc: 0.7495 [6] valid_0's auc: 0.751338 [7] valid_0's auc: 0.751338 [8] valid_0's auc: 0.749299 [9] valid_0's auc: 0.750152 [10] valid_0's auc: 0.750327 [11] valid_0's auc: 0.753588 [12] valid_0's auc: 0.751726 [13] valid_0's auc: 0.753588 [14] valid_0's auc: 0.75362 [15] valid_0's auc: 0.752114 [16] valid_0's auc: 0.75397 [17] valid_0's auc: 0.752302 [18] valid_0's auc: 0.75454 [19] valid_0's auc: 0.754551 [20] valid_0's auc: 0.755186 [21] valid_0's auc: 0.755188 [22] valid_0's auc: 0.756006 [23] valid_0's auc: 0.75601 [24] valid_0's auc: 0.75633 [25] valid_0's auc: 0.756265 [26] valid_0's auc: 0.756053 [27] valid_0's auc: 0.756274 [28] valid_0's auc: 0.75762 [29] valid_0's auc: 0.756782 [30] valid_0's auc: 0.757634 [31] valid_0's auc: 0.757675 [32] valid_0's auc: 0.758008 [33] valid_0's auc: 0.756743 [34] valid_0's auc: 0.756602 [35] valid_0's auc: 0.757746 [36] valid_0's auc: 0.757017 [37] valid_0's auc: 0.757261 [38] valid_0's auc: 0.758645 [39] valid_0's auc: 0.758549 [40] valid_0's auc: 0.758784 [41] valid_0's auc: 0.758708 [42] valid_0's auc: 0.758747 [43] valid_0's auc: 0.758709 [44] valid_0's auc: 0.758743 [45] valid_0's auc: 0.759398 [46] valid_0's auc: 0.759397 [47] valid_0's auc: 0.759717 [48] valid_0's auc: 0.759915 [49] valid_0's auc: 0.759838 [50] valid_0's auc: 0.759863 [51] valid_0's auc: 0.76599 [52] valid_0's auc: 0.766056 [53] valid_0's auc: 0.766283 [54] valid_0's auc: 0.766718 [55] valid_0's auc: 0.766806 [56] valid_0's auc: 0.766793 [57] valid_0's auc: 0.766794 [58] valid_0's auc: 0.767103 [59] valid_0's auc: 0.76718 [60] valid_0's auc: 0.767451 [61] valid_0's auc: 0.767644 [62] valid_0's auc: 0.76792 [63] valid_0's auc: 0.768226 [64] valid_0's auc: 0.768386 [65] valid_0's auc: 0.768722 [66] valid_0's auc: 0.769498 [67] valid_0's auc: 0.769579 [68] valid_0's auc: 0.769717 [69] valid_0's auc: 0.769656 [70] valid_0's auc: 0.769725 [71] valid_0's auc: 0.770004 [72] valid_0's auc: 0.770071 [73] valid_0's auc: 0.770156 [74] valid_0's auc: 0.770421 [75] valid_0's auc: 0.770445 [76] valid_0's auc: 0.770643 [77] valid_0's auc: 0.770704 [78] valid_0's auc: 0.770812 [79] valid_0's auc: 0.771044 [80] valid_0's auc: 0.771391 [81] valid_0's auc: 0.771437 [82] valid_0's auc: 0.771472 [83] valid_0's auc: 0.771566 [84] valid_0's auc: 0.771689 [85] valid_0's auc: 0.771736 [86] valid_0's auc: 0.771801 [87] valid_0's auc: 0.772011 [88] valid_0's auc: 0.772728 [89] valid_0's auc: 0.7728 [90] valid_0's auc: 0.772898 [91] valid_0's auc: 0.772956 [92] valid_0's auc: 0.773111 [93] valid_0's auc: 0.773019 [94] valid_0's auc: 0.773114 [95] valid_0's auc: 0.773192 [96] valid_0's auc: 0.773362 [97] valid_0's auc: 0.77347 [98] valid_0's auc: 0.773557 [99] valid_0's auc: 0.773817 [100] valid_0's auc: 0.773901 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.773901 [1] valid_0's auc: 0.748453 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.749691 [3] valid_0's auc: 0.751615 [4] valid_0's auc: 0.751094 [5] valid_0's auc: 0.752006 [6] valid_0's auc: 0.751589 [7] valid_0's auc: 0.756645 [8] valid_0's auc: 0.756098 [9] valid_0's auc: 0.756598 [10] valid_0's auc: 0.756621 [11] valid_0's auc: 0.756363 [12] valid_0's auc: 0.756692 [13] valid_0's auc: 0.756926 [14] valid_0's auc: 0.757646 [15] valid_0's auc: 0.75773 [16] valid_0's auc: 0.761756 [17] valid_0's auc: 0.763676 [18] valid_0's auc: 0.763493 [19] valid_0's auc: 0.765036 [20] valid_0's auc: 0.765387 [21] valid_0's auc: 0.765743 [22] valid_0's auc: 0.76701 [23] valid_0's auc: 0.768299 [24] valid_0's auc: 0.768336 [25] valid_0's auc: 0.768381 [26] valid_0's auc: 0.768425 [27] valid_0's auc: 0.768594 [28] valid_0's auc: 0.768752 [29] valid_0's auc: 0.76916 [30] valid_0's auc: 0.769535 [31] valid_0's auc: 0.769674 [32] valid_0's auc: 0.76973 [33] valid_0's auc: 0.76982 [34] valid_0's auc: 0.769762 [35] valid_0's auc: 0.769653 [36] valid_0's auc: 0.769753 [37] valid_0's auc: 0.769828 [38] valid_0's auc: 0.769715 [39] valid_0's auc: 0.769539 [40] valid_0's auc: 0.769506 [41] valid_0's auc: 0.769693 [42] valid_0's auc: 0.769792 [43] valid_0's auc: 0.769553 [44] valid_0's auc: 0.769513 [45] valid_0's auc: 0.769447 [46] valid_0's auc: 0.770235 [47] valid_0's auc: 0.770256 [48] valid_0's auc: 0.770406 [49] valid_0's auc: 0.770384 [50] valid_0's auc: 0.770514 [51] valid_0's auc: 0.770421 [52] valid_0's auc: 0.770347 [53] valid_0's auc: 0.770589 [54] valid_0's auc: 0.770489 [55] valid_0's auc: 0.770481 [56] valid_0's auc: 0.770342 [57] valid_0's auc: 0.770254 [58] valid_0's auc: 0.770084 [59] valid_0's auc: 0.770734 [60] valid_0's auc: 0.770675 [61] valid_0's auc: 0.77066 [62] valid_0's auc: 0.770407 [63] valid_0's auc: 0.770372 [64] valid_0's auc: 0.770708 [65] valid_0's auc: 0.770528 [66] valid_0's auc: 0.770437 [67] valid_0's auc: 0.770418 [68] valid_0's auc: 0.77043 [69] valid_0's auc: 0.770575 Early stopping, best iteration is: [59] valid_0's auc: 0.770734 [1] valid_0's auc: 0.748867 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.762521 [3] valid_0's auc: 0.764062 [4] valid_0's auc: 0.763258 [5] valid_0's auc: 0.762373 [6] valid_0's auc: 0.764062 [7] valid_0's auc: 0.763748 [8] valid_0's auc: 0.763192 [9] valid_0's auc: 0.762451 [10] valid_0's auc: 0.762405 [11] valid_0's auc: 0.762414 [12] valid_0's auc: 0.762585 [13] valid_0's auc: 0.764478 [14] valid_0's auc: 0.763795 [15] valid_0's auc: 0.763768 [16] valid_0's auc: 0.765035 [17] valid_0's auc: 0.764958 [18] valid_0's auc: 0.764806 [19] valid_0's auc: 0.76476 [20] valid_0's auc: 0.764852 [21] valid_0's auc: 0.765044 [22] valid_0's auc: 0.765812 [23] valid_0's auc: 0.766688 [24] valid_0's auc: 0.766439 [25] valid_0's auc: 0.766191 [26] valid_0's auc: 0.765874 [27] valid_0's auc: 0.766426 [28] valid_0's auc: 0.766262 [29] valid_0's auc: 0.767146 [30] valid_0's auc: 0.767198 [31] valid_0's auc: 0.767499 [32] valid_0's auc: 0.767265 [33] valid_0's auc: 0.767585 [34] valid_0's auc: 0.767686 [35] valid_0's auc: 0.767393 [36] valid_0's auc: 0.76741 [37] valid_0's auc: 0.767271 [38] valid_0's auc: 0.767502 [39] valid_0's auc: 0.767493 [40] valid_0's auc: 0.768043 [41] valid_0's auc: 0.768017 [42] valid_0's auc: 0.767905 [43] valid_0's auc: 0.768008 [44] valid_0's auc: 0.767984 [45] valid_0's auc: 0.76836 [46] valid_0's auc: 0.768179 [47] valid_0's auc: 0.768016 [48] valid_0's auc: 0.768079 [49] valid_0's auc: 0.768291 [50] valid_0's auc: 0.768727 [51] valid_0's auc: 0.768816 [52] valid_0's auc: 0.768913 [53] valid_0's auc: 0.769575 [54] valid_0's auc: 0.769459 [55] valid_0's auc: 0.769078 [56] valid_0's auc: 0.769225 [57] valid_0's auc: 0.769868 [58] valid_0's auc: 0.769948 [59] valid_0's auc: 0.770082 [60] valid_0's auc: 0.770177 [61] valid_0's auc: 0.770308 [62] valid_0's auc: 0.770811 [63] valid_0's auc: 0.771087 [64] valid_0's auc: 0.771062 [65] valid_0's auc: 0.771391 [66] valid_0's auc: 0.771491 [67] valid_0's auc: 0.771609 [68] valid_0's auc: 0.771634 [69] valid_0's auc: 0.771639 [70] valid_0's auc: 0.77184 [71] valid_0's auc: 0.772131 [72] valid_0's auc: 0.772183 [73] valid_0's auc: 0.772289 [74] valid_0's auc: 0.772651 [75] valid_0's auc: 0.772794 [76] valid_0's auc: 0.772885 [77] valid_0's auc: 0.77315 [78] valid_0's auc: 0.773337 [79] valid_0's auc: 0.773271 [80] valid_0's auc: 0.77366 [81] valid_0's auc: 0.773411 [82] valid_0's auc: 0.773837 [83] valid_0's auc: 0.773812 [84] valid_0's auc: 0.774001 [85] valid_0's auc: 0.774302 [86] valid_0's auc: 0.774236 [87] valid_0's auc: 0.774115 [88] valid_0's auc: 0.77435 [89] valid_0's auc: 0.774409 [90] valid_0's auc: 0.774726 [91] valid_0's auc: 0.774635 [92] valid_0's auc: 0.774694 [93] valid_0's auc: 0.774737 [94] valid_0's auc: 0.774803 [95] valid_0's auc: 0.775202 [96] valid_0's auc: 0.775197 [97] valid_0's auc: 0.775361 [98] valid_0's auc: 0.775361 [99] valid_0's auc: 0.775321 [100] valid_0's auc: 0.775437 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.775437 [1] valid_0's auc: 0.748286 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.748286 [3] valid_0's auc: 0.749259 [4] valid_0's auc: 0.749362 [5] valid_0's auc: 0.748976 [6] valid_0's auc: 0.74936 [7] valid_0's auc: 0.749362 [8] valid_0's auc: 0.749138 [9] valid_0's auc: 0.752684 [10] valid_0's auc: 0.752831 [11] valid_0's auc: 0.75366 [12] valid_0's auc: 0.75411 [13] valid_0's auc: 0.761886 [14] valid_0's auc: 0.762058 [15] valid_0's auc: 0.761342 [16] valid_0's auc: 0.762343 [17] valid_0's auc: 0.763406 [18] valid_0's auc: 0.763392 [19] valid_0's auc: 0.763273 [20] valid_0's auc: 0.76458 [21] valid_0's auc: 0.763966 [22] valid_0's auc: 0.764795 [23] valid_0's auc: 0.765132 [24] valid_0's auc: 0.765137 [25] valid_0's auc: 0.765224 [26] valid_0's auc: 0.765178 [27] valid_0's auc: 0.765203 [28] valid_0's auc: 0.765275 [29] valid_0's auc: 0.76528 [30] valid_0's auc: 0.765251 [31] valid_0's auc: 0.766388 [32] valid_0's auc: 0.76663 [33] valid_0's auc: 0.766285 [34] valid_0's auc: 0.766925 [35] valid_0's auc: 0.766744 [36] valid_0's auc: 0.766676 [37] valid_0's auc: 0.767472 [38] valid_0's auc: 0.76736 [39] valid_0's auc: 0.767359 [40] valid_0's auc: 0.76739 [41] valid_0's auc: 0.767703 [42] valid_0's auc: 0.767477 [43] valid_0's auc: 0.767541 [44] valid_0's auc: 0.767863 [45] valid_0's auc: 0.767699 [46] valid_0's auc: 0.767717 [47] valid_0's auc: 0.76795 [48] valid_0's auc: 0.767933 [49] valid_0's auc: 0.767932 [50] valid_0's auc: 0.768455 [51] valid_0's auc: 0.768476 [52] valid_0's auc: 0.76847 [53] valid_0's auc: 0.76849 [54] valid_0's auc: 0.768749 [55] valid_0's auc: 0.768557 [56] valid_0's auc: 0.769161 [57] valid_0's auc: 0.769234 [58] valid_0's auc: 0.769464 [59] valid_0's auc: 0.769393 [60] valid_0's auc: 0.769274 [61] valid_0's auc: 0.769263 [62] valid_0's auc: 0.769402 [63] valid_0's auc: 0.769438 [64] valid_0's auc: 0.76958 [65] valid_0's auc: 0.769563 [66] valid_0's auc: 0.769568 [67] valid_0's auc: 0.769779 [68] valid_0's auc: 0.769926 [69] valid_0's auc: 0.769944 [70] valid_0's auc: 0.770306 [71] valid_0's auc: 0.770275 [72] valid_0's auc: 0.770372 [73] valid_0's auc: 0.771305 [74] valid_0's auc: 0.771477 [75] valid_0's auc: 0.771405 [76] valid_0's auc: 0.771388 [77] valid_0's auc: 0.771519 [78] valid_0's auc: 0.771588 [79] valid_0's auc: 0.772025 [80] valid_0's auc: 0.772217 [81] valid_0's auc: 0.772321 [82] valid_0's auc: 0.772388 [83] valid_0's auc: 0.772701 [84] valid_0's auc: 0.772712 [85] valid_0's auc: 0.772697 [86] valid_0's auc: 0.773027 [87] valid_0's auc: 0.773182 [88] valid_0's auc: 0.773352 [89] valid_0's auc: 0.773592 [90] valid_0's auc: 0.773594 [91] valid_0's auc: 0.773858 [92] valid_0's auc: 0.773981 [93] valid_0's auc: 0.774091 [94] valid_0's auc: 0.77409 [95] valid_0's auc: 0.774341 [96] valid_0's auc: 0.774392 [97] valid_0's auc: 0.774483 [98] valid_0's auc: 0.774577 [99] valid_0's auc: 0.774593 [100] valid_0's auc: 0.774762 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.774762 [1] valid_0's auc: 0.757043 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.757043 [3] valid_0's auc: 0.757043 [4] valid_0's auc: 0.757043 [5] valid_0's auc: 0.757043 [6] valid_0's auc: 0.757043 [7] valid_0's auc: 0.757043 [8] valid_0's auc: 0.757043 [9] valid_0's auc: 0.757043 [10] valid_0's auc: 0.757043 [11] valid_0's auc: 0.758625 [12] valid_0's auc: 0.759292 [13] valid_0's auc: 0.760187 [14] valid_0's auc: 0.760275 [15] valid_0's auc: 0.760962 [16] valid_0's auc: 0.761238 [17] valid_0's auc: 0.761211 [18] valid_0's auc: 0.7613 [19] valid_0's auc: 0.761395 [20] valid_0's auc: 0.761334 [21] valid_0's auc: 0.761432 [22] valid_0's auc: 0.761521 [23] valid_0's auc: 0.761593 [24] valid_0's auc: 0.761667 [25] valid_0's auc: 0.761781 [26] valid_0's auc: 0.762145 [27] valid_0's auc: 0.762147 [28] valid_0's auc: 0.762012 [29] valid_0's auc: 0.762029 [30] valid_0's auc: 0.76205 [31] valid_0's auc: 0.7623 [32] valid_0's auc: 0.762442 [33] valid_0's auc: 0.762826 [34] valid_0's auc: 0.762886 [35] valid_0's auc: 0.762847 [36] valid_0's auc: 0.762868 [37] valid_0's auc: 0.762924 [38] valid_0's auc: 0.763281 [39] valid_0's auc: 0.76328 [40] valid_0's auc: 0.763148 [41] valid_0's auc: 0.763354 [42] valid_0's auc: 0.764574 [43] valid_0's auc: 0.764801 [44] valid_0's auc: 0.764879 [45] valid_0's auc: 0.765002 [46] valid_0's auc: 0.76495 [47] valid_0's auc: 0.765176 [48] valid_0's auc: 0.765224 [49] valid_0's auc: 0.76525 [50] valid_0's auc: 0.765488 [51] valid_0's auc: 0.765558 [52] valid_0's auc: 0.765553 [53] valid_0's auc: 0.765663 [54] valid_0's auc: 0.765647 [55] valid_0's auc: 0.766129 [56] valid_0's auc: 0.766111 [57] valid_0's auc: 0.765746 [58] valid_0's auc: 0.76651 [59] valid_0's auc: 0.766548 [60] valid_0's auc: 0.766745 [61] valid_0's auc: 0.771389 [62] valid_0's auc: 0.771551 [63] valid_0's auc: 0.771669 [64] valid_0's auc: 0.771897 [65] valid_0's auc: 0.771982 [66] valid_0's auc: 0.772083 [67] valid_0's auc: 0.772517 [68] valid_0's auc: 0.772629 [69] valid_0's auc: 0.773429 [70] valid_0's auc: 0.773844 [71] valid_0's auc: 0.773989 [72] valid_0's auc: 0.774098 [73] valid_0's auc: 0.775047 [74] valid_0's auc: 0.775309 [75] valid_0's auc: 0.775532 [76] valid_0's auc: 0.775546 [77] valid_0's auc: 0.77575 [78] valid_0's auc: 0.775891 [79] valid_0's auc: 0.776002 [80] valid_0's auc: 0.776212 [81] valid_0's auc: 0.776492 [82] valid_0's auc: 0.776616 [83] valid_0's auc: 0.776783 [84] valid_0's auc: 0.776891 [85] valid_0's auc: 0.776979 [86] valid_0's auc: 0.777022 [87] valid_0's auc: 0.777174 [88] valid_0's auc: 0.777333 [89] valid_0's auc: 0.77745 [90] valid_0's auc: 0.77752 [91] valid_0's auc: 0.777574 [92] valid_0's auc: 0.777644 [93] valid_0's auc: 0.777846 [94] valid_0's auc: 0.777805 [95] valid_0's auc: 0.777825 [96] valid_0's auc: 0.777932 [97] valid_0's auc: 0.778095 [98] valid_0's auc: 0.778152 [99] valid_0's auc: 0.778222 [100] valid_0's auc: 0.778231 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.778231 [1] valid_0's auc: 0.752298 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.759276 [3] valid_0's auc: 0.759067 [4] valid_0's auc: 0.759079 [5] valid_0's auc: 0.759532 [6] valid_0's auc: 0.759549 [7] valid_0's auc: 0.761225 [8] valid_0's auc: 0.761092 [9] valid_0's auc: 0.761531 [10] valid_0's auc: 0.761654 [11] valid_0's auc: 0.76183 [12] valid_0's auc: 0.761651 [13] valid_0's auc: 0.761898 [14] valid_0's auc: 0.763021 [15] valid_0's auc: 0.763917 [16] valid_0's auc: 0.764055 [17] valid_0's auc: 0.764371 [18] valid_0's auc: 0.764469 [19] valid_0's auc: 0.764181 [20] valid_0's auc: 0.764792 [21] valid_0's auc: 0.764872 [22] valid_0's auc: 0.766306 [23] valid_0's auc: 0.766454 [24] valid_0's auc: 0.766814 [25] valid_0's auc: 0.770826 [26] valid_0's auc: 0.77106 [27] valid_0's auc: 0.771193 [28] valid_0's auc: 0.771275 [29] valid_0's auc: 0.771764 [30] valid_0's auc: 0.772921 [31] valid_0's auc: 0.772755 [32] valid_0's auc: 0.772821 [33] valid_0's auc: 0.773079 [34] valid_0's auc: 0.774193 [35] valid_0's auc: 0.774257 [36] valid_0's auc: 0.774432 [37] valid_0's auc: 0.774706 [38] valid_0's auc: 0.775102 [39] valid_0's auc: 0.775298 [40] valid_0's auc: 0.775427 [41] valid_0's auc: 0.77582 [42] valid_0's auc: 0.775949 [43] valid_0's auc: 0.776069 [44] valid_0's auc: 0.776087 [45] valid_0's auc: 0.776161 [46] valid_0's auc: 0.776193 [47] valid_0's auc: 0.776459 [48] valid_0's auc: 0.776804 [49] valid_0's auc: 0.777155 [50] valid_0's auc: 0.777061 [51] valid_0's auc: 0.777348 [52] valid_0's auc: 0.777465 [53] valid_0's auc: 0.777494 [54] valid_0's auc: 0.777575 [55] valid_0's auc: 0.777784 [56] valid_0's auc: 0.777784 [57] valid_0's auc: 0.777785 [58] valid_0's auc: 0.77793 [59] valid_0's auc: 0.778083 [60] valid_0's auc: 0.778009 [61] valid_0's auc: 0.778058 [62] valid_0's auc: 0.778052 [63] valid_0's auc: 0.777929 [64] valid_0's auc: 0.778139 [65] valid_0's auc: 0.778281 [66] valid_0's auc: 0.778265 [67] valid_0's auc: 0.778265 [68] valid_0's auc: 0.77838 [69] valid_0's auc: 0.778393 [70] valid_0's auc: 0.778366 [71] valid_0's auc: 0.778427 [72] valid_0's auc: 0.778364 [73] valid_0's auc: 0.778342 [74] valid_0's auc: 0.778339 [75] valid_0's auc: 0.778291 [76] valid_0's auc: 0.778306 [77] valid_0's auc: 0.778345 [78] valid_0's auc: 0.778399 [79] valid_0's auc: 0.778372 [80] valid_0's auc: 0.778413 [81] valid_0's auc: 0.778537 [82] valid_0's auc: 0.77857 [83] valid_0's auc: 0.778721 [84] valid_0's auc: 0.778712 [85] valid_0's auc: 0.778755 [86] valid_0's auc: 0.778862 [87] valid_0's auc: 0.779 [88] valid_0's auc: 0.780026 [89] valid_0's auc: 0.780002 [90] valid_0's auc: 0.780006 [91] valid_0's auc: 0.780188 [92] valid_0's auc: 0.780227 [93] valid_0's auc: 0.780227 [94] valid_0's auc: 0.780421 [95] valid_0's auc: 0.780511 [96] valid_0's auc: 0.780642 [97] valid_0's auc: 0.780721 [98] valid_0's auc: 0.780743 [99] valid_0's auc: 0.780898 [100] valid_0's auc: 0.780924 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.780924 [1] valid_0's auc: 0.754636 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.7683 [3] valid_0's auc: 0.76755 [4] valid_0's auc: 0.771673 [5] valid_0's auc: 0.772091 [6] valid_0's auc: 0.771553 [7] valid_0's auc: 0.771367 [8] valid_0's auc: 0.770636 [9] valid_0's auc: 0.771707 [10] valid_0's auc: 0.771595 [11] valid_0's auc: 0.771764 [12] valid_0's auc: 0.771648 [13] valid_0's auc: 0.771187 [14] valid_0's auc: 0.77186 [15] valid_0's auc: 0.771543 Early stopping, best iteration is: [5] valid_0's auc: 0.772091 [1] valid_0's auc: 0.757698 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.757698 [3] valid_0's auc: 0.758663 [4] valid_0's auc: 0.757968 [5] valid_0's auc: 0.757959 [6] valid_0's auc: 0.757982 [7] valid_0's auc: 0.758325 [8] valid_0's auc: 0.758427 [9] valid_0's auc: 0.760477 [10] valid_0's auc: 0.761208 [11] valid_0's auc: 0.762052 [12] valid_0's auc: 0.762095 [13] valid_0's auc: 0.762074 [14] valid_0's auc: 0.762127 [15] valid_0's auc: 0.762133 [16] valid_0's auc: 0.762254 [17] valid_0's auc: 0.762284 [18] valid_0's auc: 0.761951 [19] valid_0's auc: 0.761953 [20] valid_0's auc: 0.762233 [21] valid_0's auc: 0.763617 [22] valid_0's auc: 0.763017 [23] valid_0's auc: 0.76413 [24] valid_0's auc: 0.764133 [25] valid_0's auc: 0.764182 [26] valid_0's auc: 0.764466 [27] valid_0's auc: 0.76447 [28] valid_0's auc: 0.764439 [29] valid_0's auc: 0.764552 [30] valid_0's auc: 0.764529 [31] valid_0's auc: 0.764645 [32] valid_0's auc: 0.76461 [33] valid_0's auc: 0.764749 [34] valid_0's auc: 0.764821 [35] valid_0's auc: 0.764874 [36] valid_0's auc: 0.765379 [37] valid_0's auc: 0.76569 [38] valid_0's auc: 0.771086 [39] valid_0's auc: 0.771052 [40] valid_0's auc: 0.770973 [41] valid_0's auc: 0.770923 [42] valid_0's auc: 0.771175 [43] valid_0's auc: 0.771435 [44] valid_0's auc: 0.771566 [45] valid_0's auc: 0.771553 [46] valid_0's auc: 0.77223 [47] valid_0's auc: 0.772217 [48] valid_0's auc: 0.772403 [49] valid_0's auc: 0.772724 [50] valid_0's auc: 0.772727 [51] valid_0's auc: 0.772736 [52] valid_0's auc: 0.772851 [53] valid_0's auc: 0.772891 [54] valid_0's auc: 0.773151 [55] valid_0's auc: 0.773219 [56] valid_0's auc: 0.773409 [57] valid_0's auc: 0.773384 [58] valid_0's auc: 0.773475 [59] valid_0's auc: 0.773402 [60] valid_0's auc: 0.773757 [61] valid_0's auc: 0.773803 [62] valid_0's auc: 0.774054 [63] valid_0's auc: 0.774023 [64] valid_0's auc: 0.774089 [65] valid_0's auc: 0.774476 [66] valid_0's auc: 0.774687 [67] valid_0's auc: 0.774747 [68] valid_0's auc: 0.774837 [69] valid_0's auc: 0.774838 [70] valid_0's auc: 0.775095 [71] valid_0's auc: 0.775076 [72] valid_0's auc: 0.775126 [73] valid_0's auc: 0.775658 [74] valid_0's auc: 0.775383 [75] valid_0's auc: 0.776725 [76] valid_0's auc: 0.776896 [77] valid_0's auc: 0.777285 [78] valid_0's auc: 0.777833 [79] valid_0's auc: 0.778284 [80] valid_0's auc: 0.778558 [81] valid_0's auc: 0.778694 [82] valid_0's auc: 0.778815 [83] valid_0's auc: 0.779367 [84] valid_0's auc: 0.779458 [85] valid_0's auc: 0.779447 [86] valid_0's auc: 0.779756 [87] valid_0's auc: 0.779789 [88] valid_0's auc: 0.779914 [89] valid_0's auc: 0.780055 [90] valid_0's auc: 0.780157 [91] valid_0's auc: 0.780275 [92] valid_0's auc: 0.780355 [93] valid_0's auc: 0.780553 [94] valid_0's auc: 0.78061 [95] valid_0's auc: 0.780827 [96] valid_0's auc: 0.780831 [97] valid_0's auc: 0.781015 [98] valid_0's auc: 0.781166 [99] valid_0's auc: 0.781131 [100] valid_0's auc: 0.781194 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.781194 [1] valid_0's auc: 0.760154 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.760161 [3] valid_0's auc: 0.760248 [4] valid_0's auc: 0.760916 [5] valid_0's auc: 0.761004 [6] valid_0's auc: 0.76127 [7] valid_0's auc: 0.7613 [8] valid_0's auc: 0.76127 [9] valid_0's auc: 0.761278 [10] valid_0's auc: 0.761278 [11] valid_0's auc: 0.761268 [12] valid_0's auc: 0.761437 [13] valid_0's auc: 0.76341 [14] valid_0's auc: 0.764528 [15] valid_0's auc: 0.764469 [16] valid_0's auc: 0.766352 [17] valid_0's auc: 0.767053 [18] valid_0's auc: 0.766859 [19] valid_0's auc: 0.767212 [20] valid_0's auc: 0.766872 [21] valid_0's auc: 0.766866 [22] valid_0's auc: 0.767423 [23] valid_0's auc: 0.767323 [24] valid_0's auc: 0.767413 [25] valid_0's auc: 0.767656 [26] valid_0's auc: 0.767654 [27] valid_0's auc: 0.767613 [28] valid_0's auc: 0.767717 [29] valid_0's auc: 0.768226 [30] valid_0's auc: 0.768494 [31] valid_0's auc: 0.768577 [32] valid_0's auc: 0.768808 [33] valid_0's auc: 0.768591 [34] valid_0's auc: 0.768697 [35] valid_0's auc: 0.769098 [36] valid_0's auc: 0.769009 [37] valid_0's auc: 0.769042 [38] valid_0's auc: 0.769575 [39] valid_0's auc: 0.76962 [40] valid_0's auc: 0.76958 [41] valid_0's auc: 0.769666 [42] valid_0's auc: 0.769771 [43] valid_0's auc: 0.769773 [44] valid_0's auc: 0.769946 [45] valid_0's auc: 0.769864 [46] valid_0's auc: 0.770008 [47] valid_0's auc: 0.770105 [48] valid_0's auc: 0.770358 [49] valid_0's auc: 0.770544 [50] valid_0's auc: 0.770754 [51] valid_0's auc: 0.770966 [52] valid_0's auc: 0.770991 [53] valid_0's auc: 0.770996 [54] valid_0's auc: 0.771023 [55] valid_0's auc: 0.771135 [56] valid_0's auc: 0.775167 [57] valid_0's auc: 0.775182 [58] valid_0's auc: 0.775229 [59] valid_0's auc: 0.775415 [60] valid_0's auc: 0.775413 [61] valid_0's auc: 0.775489 [62] valid_0's auc: 0.775545 [63] valid_0's auc: 0.775602 [64] valid_0's auc: 0.77607 [65] valid_0's auc: 0.776277 [66] valid_0's auc: 0.777002 [67] valid_0's auc: 0.7773 [68] valid_0's auc: 0.777466 [69] valid_0's auc: 0.778277 [70] valid_0's auc: 0.778481 [71] valid_0's auc: 0.779101 [72] valid_0's auc: 0.77928 [73] valid_0's auc: 0.779498 [74] valid_0's auc: 0.779962 [75] valid_0's auc: 0.780241 [76] valid_0's auc: 0.78028 [77] valid_0's auc: 0.78044 [78] valid_0's auc: 0.780489 [79] valid_0's auc: 0.780655 [80] valid_0's auc: 0.780801 [81] valid_0's auc: 0.780863 [82] valid_0's auc: 0.781056 [83] valid_0's auc: 0.781219 [84] valid_0's auc: 0.781239 [85] valid_0's auc: 0.781329 [86] valid_0's auc: 0.781488 [87] valid_0's auc: 0.781692 [88] valid_0's auc: 0.781652 [89] valid_0's auc: 0.78181 [90] valid_0's auc: 0.781885 [91] valid_0's auc: 0.782033 [92] valid_0's auc: 0.782059 [93] valid_0's auc: 0.782156 [94] valid_0's auc: 0.78235 [95] valid_0's auc: 0.782382 [96] valid_0's auc: 0.782505 [97] valid_0's auc: 0.782803 [98] valid_0's auc: 0.782928 [99] valid_0's auc: 0.782958 [100] valid_0's auc: 0.783127 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.783127 [1] valid_0's auc: 0.759786 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.764657 [3] valid_0's auc: 0.764758 [4] valid_0's auc: 0.764375 [5] valid_0's auc: 0.766985 [6] valid_0's auc: 0.767135 [7] valid_0's auc: 0.767228 [8] valid_0's auc: 0.767524 [9] valid_0's auc: 0.767575 [10] valid_0's auc: 0.768459 [11] valid_0's auc: 0.768472 [12] valid_0's auc: 0.768308 [13] valid_0's auc: 0.768742 [14] valid_0's auc: 0.76912 [15] valid_0's auc: 0.769523 [16] valid_0's auc: 0.769527 [17] valid_0's auc: 0.769747 [18] valid_0's auc: 0.770015 [19] valid_0's auc: 0.770021 [20] valid_0's auc: 0.770216 [21] valid_0's auc: 0.770394 [22] valid_0's auc: 0.770491 [23] valid_0's auc: 0.771372 [24] valid_0's auc: 0.77146 [25] valid_0's auc: 0.772478 [26] valid_0's auc: 0.774667 [27] valid_0's auc: 0.775156 [28] valid_0's auc: 0.775394 [29] valid_0's auc: 0.776522 [30] valid_0's auc: 0.777059 [31] valid_0's auc: 0.777769 [32] valid_0's auc: 0.778398 [33] valid_0's auc: 0.77855 [34] valid_0's auc: 0.778852 [35] valid_0's auc: 0.778991 [36] valid_0's auc: 0.779339 [37] valid_0's auc: 0.779584 [38] valid_0's auc: 0.779981 [39] valid_0's auc: 0.780291 [40] valid_0's auc: 0.780597 [41] valid_0's auc: 0.780625 [42] valid_0's auc: 0.781065 [43] valid_0's auc: 0.781104 [44] valid_0's auc: 0.78122 [45] valid_0's auc: 0.781282 [46] valid_0's auc: 0.781359 [47] valid_0's auc: 0.781428 [48] valid_0's auc: 0.781493 [49] valid_0's auc: 0.781566 [50] valid_0's auc: 0.781573 [51] valid_0's auc: 0.781657 [52] valid_0's auc: 0.781654 [53] valid_0's auc: 0.781991 [54] valid_0's auc: 0.781977 [55] valid_0's auc: 0.781937 [56] valid_0's auc: 0.782062 [57] valid_0's auc: 0.782204 [58] valid_0's auc: 0.782183 [59] valid_0's auc: 0.782284 [60] valid_0's auc: 0.78236 [61] valid_0's auc: 0.782299 [62] valid_0's auc: 0.782241 [63] valid_0's auc: 0.782255 [64] valid_0's auc: 0.782392 [65] valid_0's auc: 0.782954 [66] valid_0's auc: 0.783 [67] valid_0's auc: 0.783067 [68] valid_0's auc: 0.783055 [69] valid_0's auc: 0.783199 [70] valid_0's auc: 0.784276 [71] valid_0's auc: 0.784242 [72] valid_0's auc: 0.784126 [73] valid_0's auc: 0.784678 [74] valid_0's auc: 0.784838 [75] valid_0's auc: 0.784647 [76] valid_0's auc: 0.78471 [77] valid_0's auc: 0.785257 [78] valid_0's auc: 0.785353 [79] valid_0's auc: 0.785299 [80] valid_0's auc: 0.785447 [81] valid_0's auc: 0.785441 [82] valid_0's auc: 0.785337 [83] valid_0's auc: 0.785524 [84] valid_0's auc: 0.785471 [85] valid_0's auc: 0.785644 [86] valid_0's auc: 0.785397 [87] valid_0's auc: 0.785544 [88] valid_0's auc: 0.785513 [89] valid_0's auc: 0.785843 [90] valid_0's auc: 0.785886 [91] valid_0's auc: 0.786101 [92] valid_0's auc: 0.786287 [93] valid_0's auc: 0.786388 [94] valid_0's auc: 0.786446 [95] valid_0's auc: 0.786717 [96] valid_0's auc: 0.786801 [97] valid_0's auc: 0.786936 [98] valid_0's auc: 0.786962 [99] valid_0's auc: 0.787115 [100] valid_0's auc: 0.787182 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.787182 [1] valid_0's auc: 0.762215 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.772303 [3] valid_0's auc: 0.772421 [4] valid_0's auc: 0.776396 [5] valid_0's auc: 0.776041 [6] valid_0's auc: 0.775312 [7] valid_0's auc: 0.775295 [8] valid_0's auc: 0.774564 [9] valid_0's auc: 0.775867 [10] valid_0's auc: 0.776069 [11] valid_0's auc: 0.77626 [12] valid_0's auc: 0.775754 [13] valid_0's auc: 0.775736 [14] valid_0's auc: 0.775701 Early stopping, best iteration is: [4] valid_0's auc: 0.776396 [1] valid_0's auc: 0.760477 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.760477 [3] valid_0's auc: 0.760477 [4] valid_0's auc: 0.760477 [5] valid_0's auc: 0.761103 [6] valid_0's auc: 0.761047 [7] valid_0's auc: 0.761742 [8] valid_0's auc: 0.762091 [9] valid_0's auc: 0.761811 [10] valid_0's auc: 0.762913 [11] valid_0's auc: 0.764336 [12] valid_0's auc: 0.764575 [13] valid_0's auc: 0.76471 [14] valid_0's auc: 0.764793 [15] valid_0's auc: 0.764833 [16] valid_0's auc: 0.764858 [17] valid_0's auc: 0.765272 [18] valid_0's auc: 0.765434 [19] valid_0's auc: 0.765433 [20] valid_0's auc: 0.765377 [21] valid_0's auc: 0.766184 [22] valid_0's auc: 0.766292 [23] valid_0's auc: 0.766241 [24] valid_0's auc: 0.766845 [25] valid_0's auc: 0.766847 [26] valid_0's auc: 0.76682 [27] valid_0's auc: 0.766822 [28] valid_0's auc: 0.766843 [29] valid_0's auc: 0.767279 [30] valid_0's auc: 0.767148 [31] valid_0's auc: 0.771446 [32] valid_0's auc: 0.771758 [33] valid_0's auc: 0.772053 [34] valid_0's auc: 0.772218 [35] valid_0's auc: 0.77235 [36] valid_0's auc: 0.772422 [37] valid_0's auc: 0.772691 [38] valid_0's auc: 0.772759 [39] valid_0's auc: 0.77303 [40] valid_0's auc: 0.773159 [41] valid_0's auc: 0.773573 [42] valid_0's auc: 0.773811 [43] valid_0's auc: 0.774071 [44] valid_0's auc: 0.775543 [45] valid_0's auc: 0.775683 [46] valid_0's auc: 0.775777 [47] valid_0's auc: 0.776504 [48] valid_0's auc: 0.776461 [49] valid_0's auc: 0.776618 [50] valid_0's auc: 0.776668 [51] valid_0's auc: 0.776907 [52] valid_0's auc: 0.777106 [53] valid_0's auc: 0.777089 [54] valid_0's auc: 0.77738 [55] valid_0's auc: 0.777284 [56] valid_0's auc: 0.777854 [57] valid_0's auc: 0.777969 [58] valid_0's auc: 0.777917 [59] valid_0's auc: 0.77859 [60] valid_0's auc: 0.778583 [61] valid_0's auc: 0.778918 [62] valid_0's auc: 0.779783 [63] valid_0's auc: 0.779196 [64] valid_0's auc: 0.780008 [65] valid_0's auc: 0.780037 [66] valid_0's auc: 0.781486 [67] valid_0's auc: 0.781619 [68] valid_0's auc: 0.781764 [69] valid_0's auc: 0.781837 [70] valid_0's auc: 0.782085 [71] valid_0's auc: 0.782169 [72] valid_0's auc: 0.782249 [73] valid_0's auc: 0.782379 [74] valid_0's auc: 0.782491 [75] valid_0's auc: 0.782881 [76] valid_0's auc: 0.783108 [77] valid_0's auc: 0.783322 [78] valid_0's auc: 0.78374 [79] valid_0's auc: 0.783882 [80] valid_0's auc: 0.784251 [81] valid_0's auc: 0.784354 [82] valid_0's auc: 0.78441 [83] valid_0's auc: 0.784621 [84] valid_0's auc: 0.784695 [85] valid_0's auc: 0.784797 [86] valid_0's auc: 0.784856 [87] valid_0's auc: 0.785046 [88] valid_0's auc: 0.785056 [89] valid_0's auc: 0.785259 [90] valid_0's auc: 0.785669 [91] valid_0's auc: 0.785821 [92] valid_0's auc: 0.786026 [93] valid_0's auc: 0.786013 [94] valid_0's auc: 0.786032 [95] valid_0's auc: 0.786231 [96] valid_0's auc: 0.786296 [97] valid_0's auc: 0.78644 [98] valid_0's auc: 0.786566 [99] valid_0's auc: 0.786242 [100] valid_0's auc: 0.786363 Did not meet early stopping. Best iteration is: [98] valid_0's auc: 0.786566 [1] valid_0's auc: 0.7495 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.7495 [3] valid_0's auc: 0.7495 [4] valid_0's auc: 0.751338 [5] valid_0's auc: 0.750327 [6] valid_0's auc: 0.753589 [7] valid_0's auc: 0.753588 [8] valid_0's auc: 0.752126 [9] valid_0's auc: 0.75398 [10] valid_0's auc: 0.75454 [11] valid_0's auc: 0.756811 [12] valid_0's auc: 0.756353 [13] valid_0's auc: 0.756115 [14] valid_0's auc: 0.757521 [15] valid_0's auc: 0.757711 [16] valid_0's auc: 0.756782 [17] valid_0's auc: 0.7568 [18] valid_0's auc: 0.757043 [19] valid_0's auc: 0.757027 [20] valid_0's auc: 0.758293 [21] valid_0's auc: 0.758578 [22] valid_0's auc: 0.759191 [23] valid_0's auc: 0.759381 [24] valid_0's auc: 0.759352 [25] valid_0's auc: 0.759822 [26] valid_0's auc: 0.765487 [27] valid_0's auc: 0.765832 [28] valid_0's auc: 0.765963 [29] valid_0's auc: 0.766606 [30] valid_0's auc: 0.76669 [31] valid_0's auc: 0.767097 [32] valid_0's auc: 0.767415 [33] valid_0's auc: 0.768787 [34] valid_0's auc: 0.769275 [35] valid_0's auc: 0.769565 [36] valid_0's auc: 0.769868 [37] valid_0's auc: 0.770062 [38] valid_0's auc: 0.770654 [39] valid_0's auc: 0.770632 [40] valid_0's auc: 0.770959 [41] valid_0's auc: 0.771508 [42] valid_0's auc: 0.771749 [43] valid_0's auc: 0.771902 [44] valid_0's auc: 0.772103 [45] valid_0's auc: 0.772405 [46] valid_0's auc: 0.772598 [47] valid_0's auc: 0.773215 [48] valid_0's auc: 0.772942 [49] valid_0's auc: 0.773625 [50] valid_0's auc: 0.773889 [51] valid_0's auc: 0.774058 [52] valid_0's auc: 0.774374 [53] valid_0's auc: 0.774491 [54] valid_0's auc: 0.774528 [55] valid_0's auc: 0.774664 [56] valid_0's auc: 0.774743 [57] valid_0's auc: 0.77485 [58] valid_0's auc: 0.774814 [59] valid_0's auc: 0.775169 [60] valid_0's auc: 0.775318 [61] valid_0's auc: 0.775335 [62] valid_0's auc: 0.775345 [63] valid_0's auc: 0.775576 [64] valid_0's auc: 0.775475 [65] valid_0's auc: 0.775716 [66] valid_0's auc: 0.776086 [67] valid_0's auc: 0.776929 [68] valid_0's auc: 0.777137 [69] valid_0's auc: 0.777369 [70] valid_0's auc: 0.777667 [71] valid_0's auc: 0.777675 [72] valid_0's auc: 0.777853 [73] valid_0's auc: 0.778052 [74] valid_0's auc: 0.778135 [75] valid_0's auc: 0.778392 [76] valid_0's auc: 0.778778 [77] valid_0's auc: 0.779009 [78] valid_0's auc: 0.779211 [79] valid_0's auc: 0.779843 [80] valid_0's auc: 0.780246 [81] valid_0's auc: 0.780348 [82] valid_0's auc: 0.780768 [83] valid_0's auc: 0.780885 [84] valid_0's auc: 0.781244 [85] valid_0's auc: 0.781336 [86] valid_0's auc: 0.781627 [87] valid_0's auc: 0.781866 [88] valid_0's auc: 0.78224 [89] valid_0's auc: 0.782444 [90] valid_0's auc: 0.782611 [91] valid_0's auc: 0.782799 [92] valid_0's auc: 0.782907 [93] valid_0's auc: 0.783534 [94] valid_0's auc: 0.783718 [95] valid_0's auc: 0.783851 [96] valid_0's auc: 0.783926 [97] valid_0's auc: 0.784038 [98] valid_0's auc: 0.784118 [99] valid_0's auc: 0.784346 [100] valid_0's auc: 0.784431 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.784431 [1] valid_0's auc: 0.748453 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.750923 [3] valid_0's auc: 0.75159 [4] valid_0's auc: 0.752015 [5] valid_0's auc: 0.756742 [6] valid_0's auc: 0.756571 [7] valid_0's auc: 0.756802 [8] valid_0's auc: 0.763296 [9] valid_0's auc: 0.764728 [10] valid_0's auc: 0.764674 [11] valid_0's auc: 0.766835 [12] valid_0's auc: 0.767924 [13] valid_0's auc: 0.768343 [14] valid_0's auc: 0.768391 [15] valid_0's auc: 0.768883 [16] valid_0's auc: 0.768783 [17] valid_0's auc: 0.76873 [18] valid_0's auc: 0.769956 [19] valid_0's auc: 0.769605 [20] valid_0's auc: 0.769301 [21] valid_0's auc: 0.76932 [22] valid_0's auc: 0.769179 [23] valid_0's auc: 0.769169 [24] valid_0's auc: 0.769532 [25] valid_0's auc: 0.770316 [26] valid_0's auc: 0.77018 [27] valid_0's auc: 0.770184 [28] valid_0's auc: 0.770105 [29] valid_0's auc: 0.770008 [30] valid_0's auc: 0.770257 [31] valid_0's auc: 0.770322 [32] valid_0's auc: 0.77028 [33] valid_0's auc: 0.770151 [34] valid_0's auc: 0.769933 [35] valid_0's auc: 0.770547 [36] valid_0's auc: 0.770253 [37] valid_0's auc: 0.77016 [38] valid_0's auc: 0.77015 [39] valid_0's auc: 0.770165 [40] valid_0's auc: 0.771132 [41] valid_0's auc: 0.771074 [42] valid_0's auc: 0.771942 [43] valid_0's auc: 0.77229 [44] valid_0's auc: 0.772747 [45] valid_0's auc: 0.77291 [46] valid_0's auc: 0.772846 [47] valid_0's auc: 0.773313 [48] valid_0's auc: 0.773607 [49] valid_0's auc: 0.773905 [50] valid_0's auc: 0.774035 [51] valid_0's auc: 0.774545 [52] valid_0's auc: 0.774976 [53] valid_0's auc: 0.775024 [54] valid_0's auc: 0.775006 [55] valid_0's auc: 0.775036 [56] valid_0's auc: 0.775146 [57] valid_0's auc: 0.775301 [58] valid_0's auc: 0.775343 [59] valid_0's auc: 0.775362 [60] valid_0's auc: 0.775339 [61] valid_0's auc: 0.775374 [62] valid_0's auc: 0.77556 [63] valid_0's auc: 0.775483 [64] valid_0's auc: 0.775588 [65] valid_0's auc: 0.775736 [66] valid_0's auc: 0.775864 [67] valid_0's auc: 0.775917 [68] valid_0's auc: 0.776221 [69] valid_0's auc: 0.77633 [70] valid_0's auc: 0.776398 [71] valid_0's auc: 0.776545 [72] valid_0's auc: 0.776576 [73] valid_0's auc: 0.776699 [74] valid_0's auc: 0.776906 [75] valid_0's auc: 0.777059 [76] valid_0's auc: 0.777275 [77] valid_0's auc: 0.777435 [78] valid_0's auc: 0.777753 [79] valid_0's auc: 0.778025 [80] valid_0's auc: 0.778391 [81] valid_0's auc: 0.778697 [82] valid_0's auc: 0.778793 [83] valid_0's auc: 0.779371 [84] valid_0's auc: 0.779458 [85] valid_0's auc: 0.779461 [86] valid_0's auc: 0.779618 [87] valid_0's auc: 0.779756 [88] valid_0's auc: 0.779823 [89] valid_0's auc: 0.780088 [90] valid_0's auc: 0.780299 [91] valid_0's auc: 0.780479 [92] valid_0's auc: 0.780664 [93] valid_0's auc: 0.780709 [94] valid_0's auc: 0.780866 [95] valid_0's auc: 0.781006 [96] valid_0's auc: 0.781236 [97] valid_0's auc: 0.782116 [98] valid_0's auc: 0.782326 [99] valid_0's auc: 0.782534 [100] valid_0's auc: 0.782663 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.782663 [1] valid_0's auc: 0.748867 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.764626 [3] valid_0's auc: 0.764062 [4] valid_0's auc: 0.763174 [5] valid_0's auc: 0.762373 [6] valid_0's auc: 0.762181 [7] valid_0's auc: 0.764499 [8] valid_0's auc: 0.765714 [9] valid_0's auc: 0.764286 [10] valid_0's auc: 0.764928 [11] valid_0's auc: 0.766917 [12] valid_0's auc: 0.766881 [13] valid_0's auc: 0.766906 [14] valid_0's auc: 0.766283 [15] valid_0's auc: 0.7667 [16] valid_0's auc: 0.766629 [17] valid_0's auc: 0.76851 [18] valid_0's auc: 0.767944 [19] valid_0's auc: 0.767824 [20] valid_0's auc: 0.767996 [21] valid_0's auc: 0.768007 [22] valid_0's auc: 0.768952 [23] valid_0's auc: 0.76905 [24] valid_0's auc: 0.768594 [25] valid_0's auc: 0.768646 [26] valid_0's auc: 0.76866 [27] valid_0's auc: 0.769354 [28] valid_0's auc: 0.769503 [29] valid_0's auc: 0.769825 [30] valid_0's auc: 0.770078 [31] valid_0's auc: 0.769801 [32] valid_0's auc: 0.77048 [33] valid_0's auc: 0.770717 [34] valid_0's auc: 0.771285 [35] valid_0's auc: 0.771389 [36] valid_0's auc: 0.77182 [37] valid_0's auc: 0.77203 [38] valid_0's auc: 0.7722 [39] valid_0's auc: 0.773014 [40] valid_0's auc: 0.773625 [41] valid_0's auc: 0.773507 [42] valid_0's auc: 0.773607 [43] valid_0's auc: 0.773877 [44] valid_0's auc: 0.774023 [45] valid_0's auc: 0.774382 [46] valid_0's auc: 0.77457 [47] valid_0's auc: 0.774593 [48] valid_0's auc: 0.774779 [49] valid_0's auc: 0.774983 [50] valid_0's auc: 0.775365 [51] valid_0's auc: 0.775569 [52] valid_0's auc: 0.775595 [53] valid_0's auc: 0.775641 [54] valid_0's auc: 0.775844 [55] valid_0's auc: 0.776253 [56] valid_0's auc: 0.776337 [57] valid_0's auc: 0.776337 [58] valid_0's auc: 0.776538 [59] valid_0's auc: 0.776883 [60] valid_0's auc: 0.776977 [61] valid_0's auc: 0.777001 [62] valid_0's auc: 0.777229 [63] valid_0's auc: 0.777058 [64] valid_0's auc: 0.777297 [65] valid_0's auc: 0.777596 [66] valid_0's auc: 0.777646 [67] valid_0's auc: 0.777874 [68] valid_0's auc: 0.778043 [69] valid_0's auc: 0.778215 [70] valid_0's auc: 0.778515 [71] valid_0's auc: 0.778737 [72] valid_0's auc: 0.778903 [73] valid_0's auc: 0.778908 [74] valid_0's auc: 0.779253 [75] valid_0's auc: 0.779351 [76] valid_0's auc: 0.779524 [77] valid_0's auc: 0.779789 [78] valid_0's auc: 0.77991 [79] valid_0's auc: 0.780069 [80] valid_0's auc: 0.780281 [81] valid_0's auc: 0.780374 [82] valid_0's auc: 0.780488 [83] valid_0's auc: 0.78076 [84] valid_0's auc: 0.780907 [85] valid_0's auc: 0.780988 [86] valid_0's auc: 0.781132 [87] valid_0's auc: 0.781348 [88] valid_0's auc: 0.781664 [89] valid_0's auc: 0.781894 [90] valid_0's auc: 0.781961 [91] valid_0's auc: 0.782322 [92] valid_0's auc: 0.782617 [93] valid_0's auc: 0.782803 [94] valid_0's auc: 0.783198 [95] valid_0's auc: 0.783487 [96] valid_0's auc: 0.783581 [97] valid_0's auc: 0.783865 [98] valid_0's auc: 0.784064 [99] valid_0's auc: 0.784232 [100] valid_0's auc: 0.784314 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.784314 [1] valid_0's auc: 0.748286 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.748643 [3] valid_0's auc: 0.748974 [4] valid_0's auc: 0.749498 [5] valid_0's auc: 0.7492 [6] valid_0's auc: 0.752591 [7] valid_0's auc: 0.762035 [8] valid_0's auc: 0.762144 [9] valid_0's auc: 0.763035 [10] valid_0's auc: 0.763178 [11] valid_0's auc: 0.765609 [12] valid_0's auc: 0.76527 [13] valid_0's auc: 0.765278 [14] valid_0's auc: 0.765335 [15] valid_0's auc: 0.76555 [16] valid_0's auc: 0.76619 [17] valid_0's auc: 0.766521 [18] valid_0's auc: 0.76665 [19] valid_0's auc: 0.767155 [20] valid_0's auc: 0.767364 [21] valid_0's auc: 0.767367 [22] valid_0's auc: 0.767232 [23] valid_0's auc: 0.767634 [24] valid_0's auc: 0.767756 [25] valid_0's auc: 0.767714 [26] valid_0's auc: 0.767938 [27] valid_0's auc: 0.767937 [28] valid_0's auc: 0.767867 [29] valid_0's auc: 0.768974 [30] valid_0's auc: 0.769001 [31] valid_0's auc: 0.769098 [32] valid_0's auc: 0.769206 [33] valid_0's auc: 0.769195 [34] valid_0's auc: 0.770505 [35] valid_0's auc: 0.770678 [36] valid_0's auc: 0.770482 [37] valid_0's auc: 0.770587 [38] valid_0's auc: 0.771362 [39] valid_0's auc: 0.771987 [40] valid_0's auc: 0.77206 [41] valid_0's auc: 0.772023 [42] valid_0's auc: 0.772455 [43] valid_0's auc: 0.772861 [44] valid_0's auc: 0.773021 [45] valid_0's auc: 0.773151 [46] valid_0's auc: 0.773623 [47] valid_0's auc: 0.773685 [48] valid_0's auc: 0.774256 [49] valid_0's auc: 0.77471 [50] valid_0's auc: 0.775044 [51] valid_0's auc: 0.77515 [52] valid_0's auc: 0.775186 [53] valid_0's auc: 0.775379 [54] valid_0's auc: 0.775459 [55] valid_0's auc: 0.775584 [56] valid_0's auc: 0.775594 [57] valid_0's auc: 0.776175 [58] valid_0's auc: 0.776288 [59] valid_0's auc: 0.776372 [60] valid_0's auc: 0.77644 [61] valid_0's auc: 0.77689 [62] valid_0's auc: 0.777025 [63] valid_0's auc: 0.776944 [64] valid_0's auc: 0.777379 [65] valid_0's auc: 0.777557 [66] valid_0's auc: 0.77763 [67] valid_0's auc: 0.778218 [68] valid_0's auc: 0.778263 [69] valid_0's auc: 0.778608 [70] valid_0's auc: 0.778697 [71] valid_0's auc: 0.778846 [72] valid_0's auc: 0.779042 [73] valid_0's auc: 0.779011 [74] valid_0's auc: 0.779149 [75] valid_0's auc: 0.779399 [76] valid_0's auc: 0.779467 [77] valid_0's auc: 0.780036 [78] valid_0's auc: 0.780164 [79] valid_0's auc: 0.780311 [80] valid_0's auc: 0.780564 [81] valid_0's auc: 0.780805 [82] valid_0's auc: 0.780815 [83] valid_0's auc: 0.781148 [84] valid_0's auc: 0.781258 [85] valid_0's auc: 0.781405 [86] valid_0's auc: 0.781743 [87] valid_0's auc: 0.782363 [88] valid_0's auc: 0.782605 [89] valid_0's auc: 0.783045 [90] valid_0's auc: 0.783206 [91] valid_0's auc: 0.783568 [92] valid_0's auc: 0.784546 [93] valid_0's auc: 0.784735 [94] valid_0's auc: 0.784989 [95] valid_0's auc: 0.78531 [96] valid_0's auc: 0.78556 [97] valid_0's auc: 0.785783 [98] valid_0's auc: 0.785924 [99] valid_0's auc: 0.786128 [100] valid_0's auc: 0.786199 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.786199 [1] valid_0's auc: 0.757043 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.757043 [3] valid_0's auc: 0.757043 [4] valid_0's auc: 0.757043 [5] valid_0's auc: 0.757043 [6] valid_0's auc: 0.758795 [7] valid_0's auc: 0.760473 [8] valid_0's auc: 0.760857 [9] valid_0's auc: 0.760818 [10] valid_0's auc: 0.761516 [11] valid_0's auc: 0.761615 [12] valid_0's auc: 0.761778 [13] valid_0's auc: 0.761776 [14] valid_0's auc: 0.761917 [15] valid_0's auc: 0.762317 [16] valid_0's auc: 0.762692 [17] valid_0's auc: 0.763123 [18] valid_0's auc: 0.763131 [19] valid_0's auc: 0.763036 [20] valid_0's auc: 0.764345 [21] valid_0's auc: 0.764762 [22] valid_0's auc: 0.765017 [23] valid_0's auc: 0.764949 [24] valid_0's auc: 0.765362 [25] valid_0's auc: 0.765393 [26] valid_0's auc: 0.765275 [27] valid_0's auc: 0.765369 [28] valid_0's auc: 0.765993 [29] valid_0's auc: 0.766367 [30] valid_0's auc: 0.76649 [31] valid_0's auc: 0.771829 [32] valid_0's auc: 0.772173 [33] valid_0's auc: 0.772607 [34] valid_0's auc: 0.773638 [35] valid_0's auc: 0.774082 [36] valid_0's auc: 0.775134 [37] valid_0's auc: 0.775495 [38] valid_0's auc: 0.775634 [39] valid_0's auc: 0.776018 [40] valid_0's auc: 0.776233 [41] valid_0's auc: 0.776621 [42] valid_0's auc: 0.776757 [43] valid_0's auc: 0.777105 [44] valid_0's auc: 0.777099 [45] valid_0's auc: 0.777408 [46] valid_0's auc: 0.777497 [47] valid_0's auc: 0.777592 [48] valid_0's auc: 0.777721 [49] valid_0's auc: 0.777873 [50] valid_0's auc: 0.778025 [51] valid_0's auc: 0.778302 [52] valid_0's auc: 0.778468 [53] valid_0's auc: 0.778545 [54] valid_0's auc: 0.77858 [55] valid_0's auc: 0.778557 [56] valid_0's auc: 0.778648 [57] valid_0's auc: 0.778994 [58] valid_0's auc: 0.779233 [59] valid_0's auc: 0.779359 [60] valid_0's auc: 0.779403 [61] valid_0's auc: 0.779547 [62] valid_0's auc: 0.779773 [63] valid_0's auc: 0.779932 [64] valid_0's auc: 0.780137 [65] valid_0's auc: 0.78018 [66] valid_0's auc: 0.780524 [67] valid_0's auc: 0.78058 [68] valid_0's auc: 0.78153 [69] valid_0's auc: 0.782383 [70] valid_0's auc: 0.782668 [71] valid_0's auc: 0.782834 [72] valid_0's auc: 0.78304 [73] valid_0's auc: 0.783262 [74] valid_0's auc: 0.783359 [75] valid_0's auc: 0.783643 [76] valid_0's auc: 0.7839 [77] valid_0's auc: 0.784005 [78] valid_0's auc: 0.784293 [79] valid_0's auc: 0.784603 [80] valid_0's auc: 0.784668 [81] valid_0's auc: 0.784854 [82] valid_0's auc: 0.785038 [83] valid_0's auc: 0.785206 [84] valid_0's auc: 0.785577 [85] valid_0's auc: 0.786132 [86] valid_0's auc: 0.786435 [87] valid_0's auc: 0.786708 [88] valid_0's auc: 0.786935 [89] valid_0's auc: 0.787197 [90] valid_0's auc: 0.787367 [91] valid_0's auc: 0.787432 [92] valid_0's auc: 0.787705 [93] valid_0's auc: 0.787809 [94] valid_0's auc: 0.788053 [95] valid_0's auc: 0.788254 [96] valid_0's auc: 0.788411 [97] valid_0's auc: 0.78849 [98] valid_0's auc: 0.788737 [99] valid_0's auc: 0.788979 [100] valid_0's auc: 0.789034 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.789034 [1] valid_0's auc: 0.752298 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.759276 [3] valid_0's auc: 0.759067 [4] valid_0's auc: 0.760567 [5] valid_0's auc: 0.759938 [6] valid_0's auc: 0.762342 [7] valid_0's auc: 0.762706 [8] valid_0's auc: 0.763999 [9] valid_0's auc: 0.764612 [10] valid_0's auc: 0.764776 [11] valid_0's auc: 0.765106 [12] valid_0's auc: 0.766595 [13] valid_0's auc: 0.771201 [14] valid_0's auc: 0.771923 [15] valid_0's auc: 0.772437 [16] valid_0's auc: 0.772921 [17] valid_0's auc: 0.77431 [18] valid_0's auc: 0.774485 [19] valid_0's auc: 0.774641 [20] valid_0's auc: 0.775064 [21] valid_0's auc: 0.775545 [22] valid_0's auc: 0.77611 [23] valid_0's auc: 0.776537 [24] valid_0's auc: 0.776902 [25] valid_0's auc: 0.777254 [26] valid_0's auc: 0.777394 [27] valid_0's auc: 0.777442 [28] valid_0's auc: 0.777392 [29] valid_0's auc: 0.77758 [30] valid_0's auc: 0.777383 [31] valid_0's auc: 0.777794 [32] valid_0's auc: 0.777976 [33] valid_0's auc: 0.778251 [34] valid_0's auc: 0.777731 [35] valid_0's auc: 0.77778 [36] valid_0's auc: 0.777961 [37] valid_0's auc: 0.778129 [38] valid_0's auc: 0.778102 [39] valid_0's auc: 0.778245 [40] valid_0's auc: 0.778197 [41] valid_0's auc: 0.778061 [42] valid_0's auc: 0.778433 [43] valid_0's auc: 0.778614 [44] valid_0's auc: 0.77974 [45] valid_0's auc: 0.779764 [46] valid_0's auc: 0.779987 [47] valid_0's auc: 0.780615 [48] valid_0's auc: 0.780424 [49] valid_0's auc: 0.780608 [50] valid_0's auc: 0.780779 [51] valid_0's auc: 0.780847 [52] valid_0's auc: 0.78214 [53] valid_0's auc: 0.78229 [54] valid_0's auc: 0.782384 [55] valid_0's auc: 0.782532 [56] valid_0's auc: 0.782402 [57] valid_0's auc: 0.782763 [58] valid_0's auc: 0.782936 [59] valid_0's auc: 0.783544 [60] valid_0's auc: 0.783772 [61] valid_0's auc: 0.783937 [62] valid_0's auc: 0.78407 [63] valid_0's auc: 0.784173 [64] valid_0's auc: 0.784303 [65] valid_0's auc: 0.784477 [66] valid_0's auc: 0.784639 [67] valid_0's auc: 0.784944 [68] valid_0's auc: 0.78509 [69] valid_0's auc: 0.785387 [70] valid_0's auc: 0.785438 [71] valid_0's auc: 0.785547 [72] valid_0's auc: 0.785585 [73] valid_0's auc: 0.785797 [74] valid_0's auc: 0.785841 [75] valid_0's auc: 0.786054 [76] valid_0's auc: 0.786276 [77] valid_0's auc: 0.78637 [78] valid_0's auc: 0.786496 [79] valid_0's auc: 0.786457 [80] valid_0's auc: 0.786627 [81] valid_0's auc: 0.786597 [82] valid_0's auc: 0.78682 [83] valid_0's auc: 0.786838 [84] valid_0's auc: 0.786967 [85] valid_0's auc: 0.787209 [86] valid_0's auc: 0.787249 [87] valid_0's auc: 0.78735 [88] valid_0's auc: 0.787413 [89] valid_0's auc: 0.787573 [90] valid_0's auc: 0.787559 [91] valid_0's auc: 0.787752 [92] valid_0's auc: 0.787807 [93] valid_0's auc: 0.788006 [94] valid_0's auc: 0.788134 [95] valid_0's auc: 0.788528 [96] valid_0's auc: 0.788524 [97] valid_0's auc: 0.788586 [98] valid_0's auc: 0.788808 [99] valid_0's auc: 0.789041 [100] valid_0's auc: 0.789128 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.789128 [1] valid_0's auc: 0.754636 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.768299 [3] valid_0's auc: 0.771575 [4] valid_0's auc: 0.770665 [5] valid_0's auc: 0.772235 [6] valid_0's auc: 0.772615 [7] valid_0's auc: 0.771535 [8] valid_0's auc: 0.771287 [9] valid_0's auc: 0.77281 [10] valid_0's auc: 0.772256 [11] valid_0's auc: 0.772123 [12] valid_0's auc: 0.771535 [13] valid_0's auc: 0.771934 [14] valid_0's auc: 0.771866 [15] valid_0's auc: 0.772343 [16] valid_0's auc: 0.772163 [17] valid_0's auc: 0.773321 [18] valid_0's auc: 0.773484 [19] valid_0's auc: 0.773362 [20] valid_0's auc: 0.773379 [21] valid_0's auc: 0.774475 [22] valid_0's auc: 0.774403 [23] valid_0's auc: 0.774162 [24] valid_0's auc: 0.774937 [25] valid_0's auc: 0.774862 [26] valid_0's auc: 0.775133 [27] valid_0's auc: 0.776475 [28] valid_0's auc: 0.77654 [29] valid_0's auc: 0.777402 [30] valid_0's auc: 0.777487 [31] valid_0's auc: 0.777462 [32] valid_0's auc: 0.777524 [33] valid_0's auc: 0.778062 [34] valid_0's auc: 0.777742 [35] valid_0's auc: 0.778348 [36] valid_0's auc: 0.778726 [37] valid_0's auc: 0.779238 [38] valid_0's auc: 0.779449 [39] valid_0's auc: 0.780067 [40] valid_0's auc: 0.779956 [41] valid_0's auc: 0.780362 [42] valid_0's auc: 0.780415 [43] valid_0's auc: 0.780669 [44] valid_0's auc: 0.780786 [45] valid_0's auc: 0.781149 [46] valid_0's auc: 0.781231 [47] valid_0's auc: 0.781386 [48] valid_0's auc: 0.781814 [49] valid_0's auc: 0.78183 [50] valid_0's auc: 0.781902 [51] valid_0's auc: 0.782061 [52] valid_0's auc: 0.782548 [53] valid_0's auc: 0.782615 [54] valid_0's auc: 0.783205 [55] valid_0's auc: 0.784022 [56] valid_0's auc: 0.784129 [57] valid_0's auc: 0.784167 [58] valid_0's auc: 0.784331 [59] valid_0's auc: 0.78442 [60] valid_0's auc: 0.784602 [61] valid_0's auc: 0.784749 [62] valid_0's auc: 0.784838 [63] valid_0's auc: 0.785104 [64] valid_0's auc: 0.785134 [65] valid_0's auc: 0.785544 [66] valid_0's auc: 0.785553 [67] valid_0's auc: 0.785657 [68] valid_0's auc: 0.785782 [69] valid_0's auc: 0.786255 [70] valid_0's auc: 0.786491 [71] valid_0's auc: 0.78674 [72] valid_0's auc: 0.786871 [73] valid_0's auc: 0.786958 [74] valid_0's auc: 0.787156 [75] valid_0's auc: 0.787279 [76] valid_0's auc: 0.78741 [77] valid_0's auc: 0.787547 [78] valid_0's auc: 0.787625 [79] valid_0's auc: 0.787682 [80] valid_0's auc: 0.787975 [81] valid_0's auc: 0.788156 [82] valid_0's auc: 0.788366 [83] valid_0's auc: 0.788578 [84] valid_0's auc: 0.788651 [85] valid_0's auc: 0.788787 [86] valid_0's auc: 0.789026 [87] valid_0's auc: 0.789063 [88] valid_0's auc: 0.789263 [89] valid_0's auc: 0.789417 [90] valid_0's auc: 0.789467 [91] valid_0's auc: 0.789676 [92] valid_0's auc: 0.789727 [93] valid_0's auc: 0.7899 [94] valid_0's auc: 0.790139 [95] valid_0's auc: 0.790146 [96] valid_0's auc: 0.790475 [97] valid_0's auc: 0.790767 [98] valid_0's auc: 0.790938 [99] valid_0's auc: 0.791177 [100] valid_0's auc: 0.791463 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.791463 [1] valid_0's auc: 0.757698 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.757948 [3] valid_0's auc: 0.758047 [4] valid_0's auc: 0.758753 [5] valid_0's auc: 0.761685 [6] valid_0's auc: 0.761875 [7] valid_0's auc: 0.761995 [8] valid_0's auc: 0.762136 [9] valid_0's auc: 0.762108 [10] valid_0's auc: 0.761805 [11] valid_0's auc: 0.762741 [12] valid_0's auc: 0.763883 [13] valid_0's auc: 0.764031 [14] valid_0's auc: 0.764196 [15] valid_0's auc: 0.764499 [16] valid_0's auc: 0.764659 [17] valid_0's auc: 0.764847 [18] valid_0's auc: 0.76478 [19] valid_0's auc: 0.770272 [20] valid_0's auc: 0.77068 [21] valid_0's auc: 0.771017 [22] valid_0's auc: 0.771228 [23] valid_0's auc: 0.771304 [24] valid_0's auc: 0.772486 [25] valid_0's auc: 0.772417 [26] valid_0's auc: 0.772656 [27] valid_0's auc: 0.773035 [28] valid_0's auc: 0.773496 [29] valid_0's auc: 0.773718 [30] valid_0's auc: 0.773737 [31] valid_0's auc: 0.774286 [32] valid_0's auc: 0.774156 [33] valid_0's auc: 0.774419 [34] valid_0's auc: 0.775035 [35] valid_0's auc: 0.775044 [36] valid_0's auc: 0.775165 [37] valid_0's auc: 0.776456 [38] valid_0's auc: 0.776438 [39] valid_0's auc: 0.777963 [40] valid_0's auc: 0.77818 [41] valid_0's auc: 0.778965 [42] valid_0's auc: 0.779395 [43] valid_0's auc: 0.779625 [44] valid_0's auc: 0.779797 [45] valid_0's auc: 0.780017 [46] valid_0's auc: 0.78014 [47] valid_0's auc: 0.780392 [48] valid_0's auc: 0.780686 [49] valid_0's auc: 0.780941 [50] valid_0's auc: 0.781057 [51] valid_0's auc: 0.781848 [52] valid_0's auc: 0.781988 [53] valid_0's auc: 0.782345 [54] valid_0's auc: 0.782747 [55] valid_0's auc: 0.782932 [56] valid_0's auc: 0.783047 [57] valid_0's auc: 0.783231 [58] valid_0's auc: 0.78329 [59] valid_0's auc: 0.783585 [60] valid_0's auc: 0.783793 [61] valid_0's auc: 0.783722 [62] valid_0's auc: 0.783898 [63] valid_0's auc: 0.784182 [64] valid_0's auc: 0.784347 [65] valid_0's auc: 0.784653 [66] valid_0's auc: 0.784791 [67] valid_0's auc: 0.784979 [68] valid_0's auc: 0.785101 [69] valid_0's auc: 0.785438 [70] valid_0's auc: 0.785619 [71] valid_0's auc: 0.785697 [72] valid_0's auc: 0.785884 [73] valid_0's auc: 0.786129 [74] valid_0's auc: 0.786262 [75] valid_0's auc: 0.786407 [76] valid_0's auc: 0.78648 [77] valid_0's auc: 0.786622 [78] valid_0's auc: 0.786888 [79] valid_0's auc: 0.787043 [80] valid_0's auc: 0.787584 [81] valid_0's auc: 0.787626 [82] valid_0's auc: 0.787669 [83] valid_0's auc: 0.788003 [84] valid_0's auc: 0.788134 [85] valid_0's auc: 0.788419 [86] valid_0's auc: 0.788445 [87] valid_0's auc: 0.788551 [88] valid_0's auc: 0.78872 [89] valid_0's auc: 0.789029 [90] valid_0's auc: 0.789218 [91] valid_0's auc: 0.789434 [92] valid_0's auc: 0.789952 [93] valid_0's auc: 0.790057 [94] valid_0's auc: 0.79029 [95] valid_0's auc: 0.790682 [96] valid_0's auc: 0.791119 [97] valid_0's auc: 0.7913 [98] valid_0's auc: 0.791605 [99] valid_0's auc: 0.791886 [100] valid_0's auc: 0.792353 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.792353 [1] valid_0's auc: 0.760154 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.760161 [3] valid_0's auc: 0.761275 [4] valid_0's auc: 0.761194 [5] valid_0's auc: 0.761366 [6] valid_0's auc: 0.761239 [7] valid_0's auc: 0.764882 [8] valid_0's auc: 0.766496 [9] valid_0's auc: 0.766245 [10] valid_0's auc: 0.766683 [11] valid_0's auc: 0.767273 [12] valid_0's auc: 0.767175 [13] valid_0's auc: 0.767688 [14] valid_0's auc: 0.767789 [15] valid_0's auc: 0.768049 [16] valid_0's auc: 0.768333 [17] valid_0's auc: 0.768804 [18] valid_0's auc: 0.768959 [19] valid_0's auc: 0.76897 [20] valid_0's auc: 0.769512 [21] valid_0's auc: 0.769478 [22] valid_0's auc: 0.769664 [23] valid_0's auc: 0.769734 [24] valid_0's auc: 0.769994 [25] valid_0's auc: 0.770369 [26] valid_0's auc: 0.770508 [27] valid_0's auc: 0.770697 [28] valid_0's auc: 0.770724 [29] valid_0's auc: 0.771207 [30] valid_0's auc: 0.77529 [31] valid_0's auc: 0.775397 [32] valid_0's auc: 0.776178 [33] valid_0's auc: 0.776989 [34] valid_0's auc: 0.778373 [35] valid_0's auc: 0.778975 [36] valid_0's auc: 0.779451 [37] valid_0's auc: 0.779929 [38] valid_0's auc: 0.780117 [39] valid_0's auc: 0.780361 [40] valid_0's auc: 0.780526 [41] valid_0's auc: 0.780772 [42] valid_0's auc: 0.781169 [43] valid_0's auc: 0.781487 [44] valid_0's auc: 0.781734 [45] valid_0's auc: 0.781781 [46] valid_0's auc: 0.782008 [47] valid_0's auc: 0.782317 [48] valid_0's auc: 0.782598 [49] valid_0's auc: 0.782875 [50] valid_0's auc: 0.783112 [51] valid_0's auc: 0.783418 [52] valid_0's auc: 0.783485 [53] valid_0's auc: 0.783836 [54] valid_0's auc: 0.783857 [55] valid_0's auc: 0.783994 [56] valid_0's auc: 0.784202 [57] valid_0's auc: 0.784192 [58] valid_0's auc: 0.784464 [59] valid_0's auc: 0.785723 [60] valid_0's auc: 0.78571 [61] valid_0's auc: 0.78602 [62] valid_0's auc: 0.7861 [63] valid_0's auc: 0.786087 [64] valid_0's auc: 0.786222 [65] valid_0's auc: 0.786323 [66] valid_0's auc: 0.786404 [67] valid_0's auc: 0.786785 [68] valid_0's auc: 0.786823 [69] valid_0's auc: 0.787 [70] valid_0's auc: 0.787013 [71] valid_0's auc: 0.787273 [72] valid_0's auc: 0.787597 [73] valid_0's auc: 0.787749 [74] valid_0's auc: 0.788552 [75] valid_0's auc: 0.788607 [76] valid_0's auc: 0.788887 [77] valid_0's auc: 0.789096 [78] valid_0's auc: 0.789653 [79] valid_0's auc: 0.789639 [80] valid_0's auc: 0.789877 [81] valid_0's auc: 0.790263 [82] valid_0's auc: 0.790395 [83] valid_0's auc: 0.790688 [84] valid_0's auc: 0.790733 [85] valid_0's auc: 0.790967 [86] valid_0's auc: 0.791113 [87] valid_0's auc: 0.791254 [88] valid_0's auc: 0.79137 [89] valid_0's auc: 0.791645 [90] valid_0's auc: 0.79172 [91] valid_0's auc: 0.791966 [92] valid_0's auc: 0.792199 [93] valid_0's auc: 0.792516 [94] valid_0's auc: 0.792844 [95] valid_0's auc: 0.793063 [96] valid_0's auc: 0.793207 [97] valid_0's auc: 0.79347 [98] valid_0's auc: 0.79384 [99] valid_0's auc: 0.794088 [100] valid_0's auc: 0.794243 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.794243 [1] valid_0's auc: 0.759786 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.764657 [3] valid_0's auc: 0.765416 [4] valid_0's auc: 0.765122 [5] valid_0's auc: 0.768802 [6] valid_0's auc: 0.768371 [7] valid_0's auc: 0.768223 [8] valid_0's auc: 0.769696 [9] valid_0's auc: 0.770084 [10] valid_0's auc: 0.76985 [11] valid_0's auc: 0.770084 [12] valid_0's auc: 0.772553 [13] valid_0's auc: 0.772833 [14] valid_0's auc: 0.774962 [15] valid_0's auc: 0.776731 [16] valid_0's auc: 0.777085 [17] valid_0's auc: 0.778218 [18] valid_0's auc: 0.778599 [19] valid_0's auc: 0.779262 [20] valid_0's auc: 0.779785 [21] valid_0's auc: 0.780662 [22] valid_0's auc: 0.780817 [23] valid_0's auc: 0.781245 [24] valid_0's auc: 0.781309 [25] valid_0's auc: 0.78137 [26] valid_0's auc: 0.781547 [27] valid_0's auc: 0.781556 [28] valid_0's auc: 0.781683 [29] valid_0's auc: 0.781957 [30] valid_0's auc: 0.782143 [31] valid_0's auc: 0.78226 [32] valid_0's auc: 0.782258 [33] valid_0's auc: 0.782146 [34] valid_0's auc: 0.783026 [35] valid_0's auc: 0.782994 [36] valid_0's auc: 0.783926 [37] valid_0's auc: 0.783892 [38] valid_0's auc: 0.784254 [39] valid_0's auc: 0.78469 [40] valid_0's auc: 0.784658 [41] valid_0's auc: 0.784715 [42] valid_0's auc: 0.784692 [43] valid_0's auc: 0.785067 [44] valid_0's auc: 0.784851 [45] valid_0's auc: 0.78527 [46] valid_0's auc: 0.786097 [47] valid_0's auc: 0.786103 [48] valid_0's auc: 0.786391 [49] valid_0's auc: 0.786103 [50] valid_0's auc: 0.786322 [51] valid_0's auc: 0.786486 [52] valid_0's auc: 0.787117 [53] valid_0's auc: 0.787146 [54] valid_0's auc: 0.787302 [55] valid_0's auc: 0.787534 [56] valid_0's auc: 0.787693 [57] valid_0's auc: 0.787819 [58] valid_0's auc: 0.787985 [59] valid_0's auc: 0.788091 [60] valid_0's auc: 0.788141 [61] valid_0's auc: 0.788182 [62] valid_0's auc: 0.788354 [63] valid_0's auc: 0.788629 [64] valid_0's auc: 0.788776 [65] valid_0's auc: 0.788969 [66] valid_0's auc: 0.78913 [67] valid_0's auc: 0.789357 [68] valid_0's auc: 0.78942 [69] valid_0's auc: 0.789737 [70] valid_0's auc: 0.789753 [71] valid_0's auc: 0.790198 [72] valid_0's auc: 0.790309 [73] valid_0's auc: 0.790432 [74] valid_0's auc: 0.790811 [75] valid_0's auc: 0.791035 [76] valid_0's auc: 0.791106 [77] valid_0's auc: 0.791114 [78] valid_0's auc: 0.791274 [79] valid_0's auc: 0.791496 [80] valid_0's auc: 0.79162 [81] valid_0's auc: 0.791681 [82] valid_0's auc: 0.791771 [83] valid_0's auc: 0.791911 [84] valid_0's auc: 0.792032 [85] valid_0's auc: 0.792057 [86] valid_0's auc: 0.792311 [87] valid_0's auc: 0.792332 [88] valid_0's auc: 0.792474 [89] valid_0's auc: 0.792526 [90] valid_0's auc: 0.79275 [91] valid_0's auc: 0.792853 [92] valid_0's auc: 0.792966 [93] valid_0's auc: 0.793104 [94] valid_0's auc: 0.793066 [95] valid_0's auc: 0.79324 [96] valid_0's auc: 0.793248 [97] valid_0's auc: 0.793377 [98] valid_0's auc: 0.79337 [99] valid_0's auc: 0.793458 [100] valid_0's auc: 0.793566 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.793566 [1] valid_0's auc: 0.762215 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.772303 [3] valid_0's auc: 0.775269 [4] valid_0's auc: 0.774358 [5] valid_0's auc: 0.77402 [6] valid_0's auc: 0.77701 [7] valid_0's auc: 0.776882 [8] valid_0's auc: 0.775852 [9] valid_0's auc: 0.776006 [10] valid_0's auc: 0.778096 [11] valid_0's auc: 0.77758 [12] valid_0's auc: 0.776888 [13] valid_0's auc: 0.776609 [14] valid_0's auc: 0.776707 [15] valid_0's auc: 0.778561 [16] valid_0's auc: 0.777955 [17] valid_0's auc: 0.777753 [18] valid_0's auc: 0.778763 [19] valid_0's auc: 0.778335 [20] valid_0's auc: 0.778246 [21] valid_0's auc: 0.779333 [22] valid_0's auc: 0.779276 [23] valid_0's auc: 0.778949 [24] valid_0's auc: 0.780416 [25] valid_0's auc: 0.780641 [26] valid_0's auc: 0.780962 [27] valid_0's auc: 0.780591 [28] valid_0's auc: 0.781559 [29] valid_0's auc: 0.781823 [30] valid_0's auc: 0.781878 [31] valid_0's auc: 0.782692 [32] valid_0's auc: 0.782631 [33] valid_0's auc: 0.782614 [34] valid_0's auc: 0.783374 [35] valid_0's auc: 0.783385 [36] valid_0's auc: 0.783939 [37] valid_0's auc: 0.783825 [38] valid_0's auc: 0.783982 [39] valid_0's auc: 0.784469 [40] valid_0's auc: 0.786002 [41] valid_0's auc: 0.786036 [42] valid_0's auc: 0.786187 [43] valid_0's auc: 0.786532 [44] valid_0's auc: 0.787004 [45] valid_0's auc: 0.787682 [46] valid_0's auc: 0.787881 [47] valid_0's auc: 0.788149 [48] valid_0's auc: 0.788099 [49] valid_0's auc: 0.788289 [50] valid_0's auc: 0.788382 [51] valid_0's auc: 0.788686 [52] valid_0's auc: 0.788752 [53] valid_0's auc: 0.789079 [54] valid_0's auc: 0.789559 [55] valid_0's auc: 0.7896 [56] valid_0's auc: 0.789684 [57] valid_0's auc: 0.78988 [58] valid_0's auc: 0.789933 [59] valid_0's auc: 0.79029 [60] valid_0's auc: 0.790306 [61] valid_0's auc: 0.790442 [62] valid_0's auc: 0.790457 [63] valid_0's auc: 0.790812 [64] valid_0's auc: 0.791001 [65] valid_0's auc: 0.791055 [66] valid_0's auc: 0.791488 [67] valid_0's auc: 0.791523 [68] valid_0's auc: 0.791666 [69] valid_0's auc: 0.791733 [70] valid_0's auc: 0.791853 [71] valid_0's auc: 0.792079 [72] valid_0's auc: 0.792187 [73] valid_0's auc: 0.792463 [74] valid_0's auc: 0.792603 [75] valid_0's auc: 0.792743 [76] valid_0's auc: 0.792738 [77] valid_0's auc: 0.792841 [78] valid_0's auc: 0.792955 [79] valid_0's auc: 0.793102 [80] valid_0's auc: 0.793241 [81] valid_0's auc: 0.793332 [82] valid_0's auc: 0.793376 [83] valid_0's auc: 0.793485 [84] valid_0's auc: 0.793612 [85] valid_0's auc: 0.793715 [86] valid_0's auc: 0.793893 [87] valid_0's auc: 0.79398 [88] valid_0's auc: 0.794051 [89] valid_0's auc: 0.794168 [90] valid_0's auc: 0.794333 [91] valid_0's auc: 0.794413 [92] valid_0's auc: 0.794751 [93] valid_0's auc: 0.794833 [94] valid_0's auc: 0.794992 [95] valid_0's auc: 0.795076 [96] valid_0's auc: 0.795215 [97] valid_0's auc: 0.795345 [98] valid_0's auc: 0.79546 [99] valid_0's auc: 0.79568 [100] valid_0's auc: 0.795711 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.795711 [1] valid_0's auc: 0.760477 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.760477 [3] valid_0's auc: 0.761049 [4] valid_0's auc: 0.762803 [5] valid_0's auc: 0.764426 [6] valid_0's auc: 0.76481 [7] valid_0's auc: 0.764804 [8] valid_0's auc: 0.76486 [9] valid_0's auc: 0.765372 [10] valid_0's auc: 0.765314 [11] valid_0's auc: 0.766307 [12] valid_0's auc: 0.766468 [13] valid_0's auc: 0.766473 [14] valid_0's auc: 0.766878 [15] valid_0's auc: 0.767154 [16] valid_0's auc: 0.771358 [17] valid_0's auc: 0.771997 [18] valid_0's auc: 0.77235 [19] valid_0's auc: 0.773067 [20] valid_0's auc: 0.77316 [21] valid_0's auc: 0.773603 [22] valid_0's auc: 0.773982 [23] valid_0's auc: 0.77437 [24] valid_0's auc: 0.776197 [25] valid_0's auc: 0.776418 [26] valid_0's auc: 0.777278 [27] valid_0's auc: 0.777414 [28] valid_0's auc: 0.777641 [29] valid_0's auc: 0.778541 [30] valid_0's auc: 0.778702 [31] valid_0's auc: 0.778776 [32] valid_0's auc: 0.779424 [33] valid_0's auc: 0.781895 [34] valid_0's auc: 0.782156 [35] valid_0's auc: 0.782471 [36] valid_0's auc: 0.78238 [37] valid_0's auc: 0.782442 [38] valid_0's auc: 0.782723 [39] valid_0's auc: 0.783611 [40] valid_0's auc: 0.783936 [41] valid_0's auc: 0.784154 [42] valid_0's auc: 0.784687 [43] valid_0's auc: 0.784856 [44] valid_0's auc: 0.785017 [45] valid_0's auc: 0.785474 [46] valid_0's auc: 0.785745 [47] valid_0's auc: 0.786119 [48] valid_0's auc: 0.786212 [49] valid_0's auc: 0.78609 [50] valid_0's auc: 0.786079 [51] valid_0's auc: 0.786433 [52] valid_0's auc: 0.786534 [53] valid_0's auc: 0.78668 [54] valid_0's auc: 0.786942 [55] valid_0's auc: 0.787322 [56] valid_0's auc: 0.78739 [57] valid_0's auc: 0.787454 [58] valid_0's auc: 0.787588 [59] valid_0's auc: 0.787963 [60] valid_0's auc: 0.788005 [61] valid_0's auc: 0.788147 [62] valid_0's auc: 0.788331 [63] valid_0's auc: 0.788597 [64] valid_0's auc: 0.789037 [65] valid_0's auc: 0.789185 [66] valid_0's auc: 0.78975 [67] valid_0's auc: 0.789884 [68] valid_0's auc: 0.789872 [69] valid_0's auc: 0.790233 [70] valid_0's auc: 0.790472 [71] valid_0's auc: 0.790604 [72] valid_0's auc: 0.790855 [73] valid_0's auc: 0.790919 [74] valid_0's auc: 0.791129 [75] valid_0's auc: 0.79132 [76] valid_0's auc: 0.791519 [77] valid_0's auc: 0.791642 [78] valid_0's auc: 0.791805 [79] valid_0's auc: 0.791894 [80] valid_0's auc: 0.792156 [81] valid_0's auc: 0.79229 [82] valid_0's auc: 0.79234 [83] valid_0's auc: 0.792528 [84] valid_0's auc: 0.792846 [85] valid_0's auc: 0.792962 [86] valid_0's auc: 0.793151 [87] valid_0's auc: 0.793373 [88] valid_0's auc: 0.793494 [89] valid_0's auc: 0.793592 [90] valid_0's auc: 0.793746 [91] valid_0's auc: 0.793984 [92] valid_0's auc: 0.794137 [93] valid_0's auc: 0.794296 [94] valid_0's auc: 0.794592 [95] valid_0's auc: 0.794654 [96] valid_0's auc: 0.79484 [97] valid_0's auc: 0.795148 [98] valid_0's auc: 0.795326 [99] valid_0's auc: 0.795606 [100] valid_0's auc: 0.795675 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.795675 [1] valid_0's auc: 0.7495 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.7495 [3] valid_0's auc: 0.7495 [4] valid_0's auc: 0.751338 [5] valid_0's auc: 0.750327 [6] valid_0's auc: 0.753589 [7] valid_0's auc: 0.753588 [8] valid_0's auc: 0.752126 [9] valid_0's auc: 0.75398 [10] valid_0's auc: 0.75454 [11] valid_0's auc: 0.756811 [12] valid_0's auc: 0.756353 [13] valid_0's auc: 0.756115 [14] valid_0's auc: 0.757521 [15] valid_0's auc: 0.757711 [16] valid_0's auc: 0.756782 [17] valid_0's auc: 0.7568 [18] valid_0's auc: 0.757043 [19] valid_0's auc: 0.757027 [20] valid_0's auc: 0.758293 [21] valid_0's auc: 0.758578 [22] valid_0's auc: 0.759191 [23] valid_0's auc: 0.759381 [24] valid_0's auc: 0.759352 [25] valid_0's auc: 0.759822 [26] valid_0's auc: 0.765487 [27] valid_0's auc: 0.765832 [28] valid_0's auc: 0.765963 [29] valid_0's auc: 0.766606 [30] valid_0's auc: 0.76669 [31] valid_0's auc: 0.767097 [32] valid_0's auc: 0.767415 [33] valid_0's auc: 0.768787 [34] valid_0's auc: 0.769275 [35] valid_0's auc: 0.769565 [36] valid_0's auc: 0.769868 [37] valid_0's auc: 0.770062 [38] valid_0's auc: 0.770654 [39] valid_0's auc: 0.770632 [40] valid_0's auc: 0.770959 [41] valid_0's auc: 0.771508 [42] valid_0's auc: 0.771749 [43] valid_0's auc: 0.771902 [44] valid_0's auc: 0.772103 [45] valid_0's auc: 0.772405 [46] valid_0's auc: 0.772598 [47] valid_0's auc: 0.773215 [48] valid_0's auc: 0.772942 [49] valid_0's auc: 0.773625 [50] valid_0's auc: 0.773889 [51] valid_0's auc: 0.774058 [52] valid_0's auc: 0.774374 [53] valid_0's auc: 0.774491 [54] valid_0's auc: 0.774528 [55] valid_0's auc: 0.774664 [56] valid_0's auc: 0.774743 [57] valid_0's auc: 0.77485 [58] valid_0's auc: 0.774814 [59] valid_0's auc: 0.775169 [60] valid_0's auc: 0.775318 [61] valid_0's auc: 0.775335 [62] valid_0's auc: 0.775345 [63] valid_0's auc: 0.775576 [64] valid_0's auc: 0.775475 [65] valid_0's auc: 0.775716 [66] valid_0's auc: 0.776086 [67] valid_0's auc: 0.776929 [68] valid_0's auc: 0.777137 [69] valid_0's auc: 0.777369 [70] valid_0's auc: 0.777667 [71] valid_0's auc: 0.777675 [72] valid_0's auc: 0.777853 [73] valid_0's auc: 0.778052 [74] valid_0's auc: 0.778135 [75] valid_0's auc: 0.778392 [76] valid_0's auc: 0.778778 [77] valid_0's auc: 0.779009 [78] valid_0's auc: 0.779211 [79] valid_0's auc: 0.779843 [80] valid_0's auc: 0.780246 [81] valid_0's auc: 0.780348 [82] valid_0's auc: 0.780768 [83] valid_0's auc: 0.780885 [84] valid_0's auc: 0.781244 [85] valid_0's auc: 0.781336 [86] valid_0's auc: 0.781627 [87] valid_0's auc: 0.781866 [88] valid_0's auc: 0.78224 [89] valid_0's auc: 0.782444 [90] valid_0's auc: 0.782611 [91] valid_0's auc: 0.782799 [92] valid_0's auc: 0.782907 [93] valid_0's auc: 0.783534 [94] valid_0's auc: 0.783718 [95] valid_0's auc: 0.783851 [96] valid_0's auc: 0.783926 [97] valid_0's auc: 0.784038 [98] valid_0's auc: 0.784118 [99] valid_0's auc: 0.784346 [100] valid_0's auc: 0.784431 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.784431 [1] valid_0's auc: 0.748453 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.750923 [3] valid_0's auc: 0.75159 [4] valid_0's auc: 0.752015 [5] valid_0's auc: 0.756742 [6] valid_0's auc: 0.756571 [7] valid_0's auc: 0.756802 [8] valid_0's auc: 0.763296 [9] valid_0's auc: 0.764728 [10] valid_0's auc: 0.764674 [11] valid_0's auc: 0.766835 [12] valid_0's auc: 0.767924 [13] valid_0's auc: 0.768343 [14] valid_0's auc: 0.768391 [15] valid_0's auc: 0.768883 [16] valid_0's auc: 0.768783 [17] valid_0's auc: 0.76873 [18] valid_0's auc: 0.769956 [19] valid_0's auc: 0.769605 [20] valid_0's auc: 0.769301 [21] valid_0's auc: 0.76932 [22] valid_0's auc: 0.769179 [23] valid_0's auc: 0.769169 [24] valid_0's auc: 0.769532 [25] valid_0's auc: 0.770316 [26] valid_0's auc: 0.77018 [27] valid_0's auc: 0.770184 [28] valid_0's auc: 0.770105 [29] valid_0's auc: 0.770008 [30] valid_0's auc: 0.770257 [31] valid_0's auc: 0.770322 [32] valid_0's auc: 0.77028 [33] valid_0's auc: 0.770151 [34] valid_0's auc: 0.769933 [35] valid_0's auc: 0.770547 [36] valid_0's auc: 0.770253 [37] valid_0's auc: 0.77016 [38] valid_0's auc: 0.77015 [39] valid_0's auc: 0.770165 [40] valid_0's auc: 0.771132 [41] valid_0's auc: 0.771074 [42] valid_0's auc: 0.771942 [43] valid_0's auc: 0.77229 [44] valid_0's auc: 0.772747 [45] valid_0's auc: 0.77291 [46] valid_0's auc: 0.772846 [47] valid_0's auc: 0.773313 [48] valid_0's auc: 0.773607 [49] valid_0's auc: 0.773905 [50] valid_0's auc: 0.774035 [51] valid_0's auc: 0.774545 [52] valid_0's auc: 0.774976 [53] valid_0's auc: 0.775024 [54] valid_0's auc: 0.775006 [55] valid_0's auc: 0.775036 [56] valid_0's auc: 0.775146 [57] valid_0's auc: 0.775301 [58] valid_0's auc: 0.775343 [59] valid_0's auc: 0.775362 [60] valid_0's auc: 0.775339 [61] valid_0's auc: 0.775374 [62] valid_0's auc: 0.77556 [63] valid_0's auc: 0.775483 [64] valid_0's auc: 0.775588 [65] valid_0's auc: 0.775736 [66] valid_0's auc: 0.775864 [67] valid_0's auc: 0.775917 [68] valid_0's auc: 0.776221 [69] valid_0's auc: 0.77633 [70] valid_0's auc: 0.776398 [71] valid_0's auc: 0.776545 [72] valid_0's auc: 0.776576 [73] valid_0's auc: 0.776699 [74] valid_0's auc: 0.776906 [75] valid_0's auc: 0.777059 [76] valid_0's auc: 0.777275 [77] valid_0's auc: 0.777435 [78] valid_0's auc: 0.777753 [79] valid_0's auc: 0.778025 [80] valid_0's auc: 0.778391 [81] valid_0's auc: 0.778697 [82] valid_0's auc: 0.778793 [83] valid_0's auc: 0.779371 [84] valid_0's auc: 0.779458 [85] valid_0's auc: 0.779461 [86] valid_0's auc: 0.779618 [87] valid_0's auc: 0.779756 [88] valid_0's auc: 0.779823 [89] valid_0's auc: 0.780088 [90] valid_0's auc: 0.780299 [91] valid_0's auc: 0.780479 [92] valid_0's auc: 0.780664 [93] valid_0's auc: 0.780709 [94] valid_0's auc: 0.780866 [95] valid_0's auc: 0.781006 [96] valid_0's auc: 0.781236 [97] valid_0's auc: 0.782116 [98] valid_0's auc: 0.782326 [99] valid_0's auc: 0.782534 [100] valid_0's auc: 0.782663 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.782663 [1] valid_0's auc: 0.748867 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.764626 [3] valid_0's auc: 0.764062 [4] valid_0's auc: 0.763174 [5] valid_0's auc: 0.762373 [6] valid_0's auc: 0.762181 [7] valid_0's auc: 0.764499 [8] valid_0's auc: 0.765714 [9] valid_0's auc: 0.764286 [10] valid_0's auc: 0.764928 [11] valid_0's auc: 0.766917 [12] valid_0's auc: 0.766881 [13] valid_0's auc: 0.766906 [14] valid_0's auc: 0.766283 [15] valid_0's auc: 0.7667 [16] valid_0's auc: 0.766629 [17] valid_0's auc: 0.76851 [18] valid_0's auc: 0.767944 [19] valid_0's auc: 0.767824 [20] valid_0's auc: 0.767996 [21] valid_0's auc: 0.768007 [22] valid_0's auc: 0.768952 [23] valid_0's auc: 0.76905 [24] valid_0's auc: 0.768594 [25] valid_0's auc: 0.768646 [26] valid_0's auc: 0.76866 [27] valid_0's auc: 0.769354 [28] valid_0's auc: 0.769503 [29] valid_0's auc: 0.769825 [30] valid_0's auc: 0.770078 [31] valid_0's auc: 0.769801 [32] valid_0's auc: 0.77048 [33] valid_0's auc: 0.770717 [34] valid_0's auc: 0.771285 [35] valid_0's auc: 0.771389 [36] valid_0's auc: 0.77182 [37] valid_0's auc: 0.77203 [38] valid_0's auc: 0.7722 [39] valid_0's auc: 0.773014 [40] valid_0's auc: 0.773625 [41] valid_0's auc: 0.773507 [42] valid_0's auc: 0.773607 [43] valid_0's auc: 0.773877 [44] valid_0's auc: 0.774023 [45] valid_0's auc: 0.774382 [46] valid_0's auc: 0.77457 [47] valid_0's auc: 0.774593 [48] valid_0's auc: 0.774779 [49] valid_0's auc: 0.774983 [50] valid_0's auc: 0.775365 [51] valid_0's auc: 0.775569 [52] valid_0's auc: 0.775595 [53] valid_0's auc: 0.775641 [54] valid_0's auc: 0.775844 [55] valid_0's auc: 0.776253 [56] valid_0's auc: 0.776337 [57] valid_0's auc: 0.776337 [58] valid_0's auc: 0.776538 [59] valid_0's auc: 0.776883 [60] valid_0's auc: 0.776977 [61] valid_0's auc: 0.777001 [62] valid_0's auc: 0.777229 [63] valid_0's auc: 0.777058 [64] valid_0's auc: 0.777297 [65] valid_0's auc: 0.777596 [66] valid_0's auc: 0.777646 [67] valid_0's auc: 0.777874 [68] valid_0's auc: 0.778043 [69] valid_0's auc: 0.778215 [70] valid_0's auc: 0.778515 [71] valid_0's auc: 0.778737 [72] valid_0's auc: 0.778903 [73] valid_0's auc: 0.778908 [74] valid_0's auc: 0.779253 [75] valid_0's auc: 0.779351 [76] valid_0's auc: 0.779524 [77] valid_0's auc: 0.779789 [78] valid_0's auc: 0.77991 [79] valid_0's auc: 0.780069 [80] valid_0's auc: 0.780281 [81] valid_0's auc: 0.780374 [82] valid_0's auc: 0.780488 [83] valid_0's auc: 0.78076 [84] valid_0's auc: 0.780907 [85] valid_0's auc: 0.780988 [86] valid_0's auc: 0.781132 [87] valid_0's auc: 0.781348 [88] valid_0's auc: 0.781664 [89] valid_0's auc: 0.781894 [90] valid_0's auc: 0.781961 [91] valid_0's auc: 0.782322 [92] valid_0's auc: 0.782617 [93] valid_0's auc: 0.782803 [94] valid_0's auc: 0.783198 [95] valid_0's auc: 0.783487 [96] valid_0's auc: 0.783581 [97] valid_0's auc: 0.783865 [98] valid_0's auc: 0.784064 [99] valid_0's auc: 0.784232 [100] valid_0's auc: 0.784314 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.784314 [1] valid_0's auc: 0.748286 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.748643 [3] valid_0's auc: 0.748974 [4] valid_0's auc: 0.749498 [5] valid_0's auc: 0.7492 [6] valid_0's auc: 0.752591 [7] valid_0's auc: 0.762035 [8] valid_0's auc: 0.762144 [9] valid_0's auc: 0.763035 [10] valid_0's auc: 0.763178 [11] valid_0's auc: 0.765609 [12] valid_0's auc: 0.76527 [13] valid_0's auc: 0.765278 [14] valid_0's auc: 0.765335 [15] valid_0's auc: 0.76555 [16] valid_0's auc: 0.76619 [17] valid_0's auc: 0.766521 [18] valid_0's auc: 0.76665 [19] valid_0's auc: 0.767155 [20] valid_0's auc: 0.767364 [21] valid_0's auc: 0.767367 [22] valid_0's auc: 0.767232 [23] valid_0's auc: 0.767634 [24] valid_0's auc: 0.767756 [25] valid_0's auc: 0.767714 [26] valid_0's auc: 0.767938 [27] valid_0's auc: 0.767937 [28] valid_0's auc: 0.767867 [29] valid_0's auc: 0.768974 [30] valid_0's auc: 0.769001 [31] valid_0's auc: 0.769098 [32] valid_0's auc: 0.769206 [33] valid_0's auc: 0.769195 [34] valid_0's auc: 0.770505 [35] valid_0's auc: 0.770678 [36] valid_0's auc: 0.770482 [37] valid_0's auc: 0.770587 [38] valid_0's auc: 0.771362 [39] valid_0's auc: 0.771987 [40] valid_0's auc: 0.77206 [41] valid_0's auc: 0.772023 [42] valid_0's auc: 0.772455 [43] valid_0's auc: 0.772861 [44] valid_0's auc: 0.773021 [45] valid_0's auc: 0.773151 [46] valid_0's auc: 0.773623 [47] valid_0's auc: 0.773685 [48] valid_0's auc: 0.774256 [49] valid_0's auc: 0.77471 [50] valid_0's auc: 0.775044 [51] valid_0's auc: 0.77515 [52] valid_0's auc: 0.775186 [53] valid_0's auc: 0.775379 [54] valid_0's auc: 0.775459 [55] valid_0's auc: 0.775584 [56] valid_0's auc: 0.775594 [57] valid_0's auc: 0.776175 [58] valid_0's auc: 0.776288 [59] valid_0's auc: 0.776372 [60] valid_0's auc: 0.77644 [61] valid_0's auc: 0.77689 [62] valid_0's auc: 0.777025 [63] valid_0's auc: 0.776944 [64] valid_0's auc: 0.777379 [65] valid_0's auc: 0.777557 [66] valid_0's auc: 0.77763 [67] valid_0's auc: 0.778218 [68] valid_0's auc: 0.778263 [69] valid_0's auc: 0.778608 [70] valid_0's auc: 0.778697 [71] valid_0's auc: 0.778846 [72] valid_0's auc: 0.779042 [73] valid_0's auc: 0.779011 [74] valid_0's auc: 0.779149 [75] valid_0's auc: 0.779399 [76] valid_0's auc: 0.779467 [77] valid_0's auc: 0.780036 [78] valid_0's auc: 0.780164 [79] valid_0's auc: 0.780311 [80] valid_0's auc: 0.780564 [81] valid_0's auc: 0.780805 [82] valid_0's auc: 0.780815 [83] valid_0's auc: 0.781148 [84] valid_0's auc: 0.781258 [85] valid_0's auc: 0.781405 [86] valid_0's auc: 0.781743 [87] valid_0's auc: 0.782363 [88] valid_0's auc: 0.782605 [89] valid_0's auc: 0.783045 [90] valid_0's auc: 0.783206 [91] valid_0's auc: 0.783568 [92] valid_0's auc: 0.784546 [93] valid_0's auc: 0.784735 [94] valid_0's auc: 0.784989 [95] valid_0's auc: 0.78531 [96] valid_0's auc: 0.78556 [97] valid_0's auc: 0.785783 [98] valid_0's auc: 0.785924 [99] valid_0's auc: 0.786128 [100] valid_0's auc: 0.786199 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.786199 [1] valid_0's auc: 0.757043 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.757043 [3] valid_0's auc: 0.757043 [4] valid_0's auc: 0.757043 [5] valid_0's auc: 0.757043 [6] valid_0's auc: 0.758795 [7] valid_0's auc: 0.760473 [8] valid_0's auc: 0.760857 [9] valid_0's auc: 0.760818 [10] valid_0's auc: 0.761516 [11] valid_0's auc: 0.761615 [12] valid_0's auc: 0.761778 [13] valid_0's auc: 0.761776 [14] valid_0's auc: 0.761917 [15] valid_0's auc: 0.762317 [16] valid_0's auc: 0.762692 [17] valid_0's auc: 0.763123 [18] valid_0's auc: 0.763131 [19] valid_0's auc: 0.763036 [20] valid_0's auc: 0.764345 [21] valid_0's auc: 0.764762 [22] valid_0's auc: 0.765017 [23] valid_0's auc: 0.764949 [24] valid_0's auc: 0.765362 [25] valid_0's auc: 0.765393 [26] valid_0's auc: 0.765275 [27] valid_0's auc: 0.765369 [28] valid_0's auc: 0.765993 [29] valid_0's auc: 0.766367 [30] valid_0's auc: 0.76649 [31] valid_0's auc: 0.771829 [32] valid_0's auc: 0.772173 [33] valid_0's auc: 0.772607 [34] valid_0's auc: 0.773638 [35] valid_0's auc: 0.774082 [36] valid_0's auc: 0.775134 [37] valid_0's auc: 0.775495 [38] valid_0's auc: 0.775634 [39] valid_0's auc: 0.776018 [40] valid_0's auc: 0.776233 [41] valid_0's auc: 0.776621 [42] valid_0's auc: 0.776757 [43] valid_0's auc: 0.777105 [44] valid_0's auc: 0.777099 [45] valid_0's auc: 0.777408 [46] valid_0's auc: 0.777497 [47] valid_0's auc: 0.777592 [48] valid_0's auc: 0.777721 [49] valid_0's auc: 0.777873 [50] valid_0's auc: 0.778025 [51] valid_0's auc: 0.778302 [52] valid_0's auc: 0.778468 [53] valid_0's auc: 0.778545 [54] valid_0's auc: 0.77858 [55] valid_0's auc: 0.778557 [56] valid_0's auc: 0.778648 [57] valid_0's auc: 0.778994 [58] valid_0's auc: 0.779233 [59] valid_0's auc: 0.779359 [60] valid_0's auc: 0.779403 [61] valid_0's auc: 0.779547 [62] valid_0's auc: 0.779773 [63] valid_0's auc: 0.779932 [64] valid_0's auc: 0.780137 [65] valid_0's auc: 0.78018 [66] valid_0's auc: 0.780524 [67] valid_0's auc: 0.78058 [68] valid_0's auc: 0.78153 [69] valid_0's auc: 0.782383 [70] valid_0's auc: 0.782668 [71] valid_0's auc: 0.782834 [72] valid_0's auc: 0.78304 [73] valid_0's auc: 0.783262 [74] valid_0's auc: 0.783359 [75] valid_0's auc: 0.783643 [76] valid_0's auc: 0.7839 [77] valid_0's auc: 0.784005 [78] valid_0's auc: 0.784293 [79] valid_0's auc: 0.784603 [80] valid_0's auc: 0.784668 [81] valid_0's auc: 0.784854 [82] valid_0's auc: 0.785038 [83] valid_0's auc: 0.785206 [84] valid_0's auc: 0.785577 [85] valid_0's auc: 0.786132 [86] valid_0's auc: 0.786435 [87] valid_0's auc: 0.786708 [88] valid_0's auc: 0.786935 [89] valid_0's auc: 0.787197 [90] valid_0's auc: 0.787367 [91] valid_0's auc: 0.787432 [92] valid_0's auc: 0.787705 [93] valid_0's auc: 0.787809 [94] valid_0's auc: 0.788053 [95] valid_0's auc: 0.788254 [96] valid_0's auc: 0.788411 [97] valid_0's auc: 0.78849 [98] valid_0's auc: 0.788737 [99] valid_0's auc: 0.788979 [100] valid_0's auc: 0.789034 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.789034 [1] valid_0's auc: 0.752298 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.759276 [3] valid_0's auc: 0.759067 [4] valid_0's auc: 0.760567 [5] valid_0's auc: 0.759938 [6] valid_0's auc: 0.762342 [7] valid_0's auc: 0.762706 [8] valid_0's auc: 0.763999 [9] valid_0's auc: 0.764612 [10] valid_0's auc: 0.764776 [11] valid_0's auc: 0.765106 [12] valid_0's auc: 0.766595 [13] valid_0's auc: 0.771201 [14] valid_0's auc: 0.771923 [15] valid_0's auc: 0.772437 [16] valid_0's auc: 0.772921 [17] valid_0's auc: 0.77431 [18] valid_0's auc: 0.774485 [19] valid_0's auc: 0.774641 [20] valid_0's auc: 0.775064 [21] valid_0's auc: 0.775545 [22] valid_0's auc: 0.77611 [23] valid_0's auc: 0.776537 [24] valid_0's auc: 0.776902 [25] valid_0's auc: 0.777254 [26] valid_0's auc: 0.777394 [27] valid_0's auc: 0.777442 [28] valid_0's auc: 0.777392 [29] valid_0's auc: 0.77758 [30] valid_0's auc: 0.777383 [31] valid_0's auc: 0.777794 [32] valid_0's auc: 0.777976 [33] valid_0's auc: 0.778251 [34] valid_0's auc: 0.777731 [35] valid_0's auc: 0.77778 [36] valid_0's auc: 0.777961 [37] valid_0's auc: 0.778129 [38] valid_0's auc: 0.778102 [39] valid_0's auc: 0.778245 [40] valid_0's auc: 0.778197 [41] valid_0's auc: 0.778061 [42] valid_0's auc: 0.778433 [43] valid_0's auc: 0.778614 [44] valid_0's auc: 0.77974 [45] valid_0's auc: 0.779764 [46] valid_0's auc: 0.779987 [47] valid_0's auc: 0.780615 [48] valid_0's auc: 0.780424 [49] valid_0's auc: 0.780608 [50] valid_0's auc: 0.780779 [51] valid_0's auc: 0.780847 [52] valid_0's auc: 0.78214 [53] valid_0's auc: 0.78229 [54] valid_0's auc: 0.782384 [55] valid_0's auc: 0.782532 [56] valid_0's auc: 0.782402 [57] valid_0's auc: 0.782763 [58] valid_0's auc: 0.782936 [59] valid_0's auc: 0.783544 [60] valid_0's auc: 0.783772 [61] valid_0's auc: 0.783937 [62] valid_0's auc: 0.78407 [63] valid_0's auc: 0.784173 [64] valid_0's auc: 0.784303 [65] valid_0's auc: 0.784477 [66] valid_0's auc: 0.784639 [67] valid_0's auc: 0.784944 [68] valid_0's auc: 0.78509 [69] valid_0's auc: 0.785387 [70] valid_0's auc: 0.785438 [71] valid_0's auc: 0.785547 [72] valid_0's auc: 0.785585 [73] valid_0's auc: 0.785797 [74] valid_0's auc: 0.785841 [75] valid_0's auc: 0.786054 [76] valid_0's auc: 0.786276 [77] valid_0's auc: 0.78637 [78] valid_0's auc: 0.786496 [79] valid_0's auc: 0.786457 [80] valid_0's auc: 0.786627 [81] valid_0's auc: 0.786597 [82] valid_0's auc: 0.78682 [83] valid_0's auc: 0.786838 [84] valid_0's auc: 0.786967 [85] valid_0's auc: 0.787209 [86] valid_0's auc: 0.787249 [87] valid_0's auc: 0.78735 [88] valid_0's auc: 0.787413 [89] valid_0's auc: 0.787573 [90] valid_0's auc: 0.787559 [91] valid_0's auc: 0.787752 [92] valid_0's auc: 0.787807 [93] valid_0's auc: 0.788006 [94] valid_0's auc: 0.788134 [95] valid_0's auc: 0.788528 [96] valid_0's auc: 0.788524 [97] valid_0's auc: 0.788586 [98] valid_0's auc: 0.788808 [99] valid_0's auc: 0.789041 [100] valid_0's auc: 0.789128 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.789128 [1] valid_0's auc: 0.754636 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.768299 [3] valid_0's auc: 0.771575 [4] valid_0's auc: 0.770665 [5] valid_0's auc: 0.772235 [6] valid_0's auc: 0.772615 [7] valid_0's auc: 0.771535 [8] valid_0's auc: 0.771287 [9] valid_0's auc: 0.77281 [10] valid_0's auc: 0.772256 [11] valid_0's auc: 0.772123 [12] valid_0's auc: 0.771535 [13] valid_0's auc: 0.771934 [14] valid_0's auc: 0.771866 [15] valid_0's auc: 0.772343 [16] valid_0's auc: 0.772163 [17] valid_0's auc: 0.773321 [18] valid_0's auc: 0.773484 [19] valid_0's auc: 0.773362 [20] valid_0's auc: 0.773379 [21] valid_0's auc: 0.774475 [22] valid_0's auc: 0.774403 [23] valid_0's auc: 0.774162 [24] valid_0's auc: 0.774937 [25] valid_0's auc: 0.774862 [26] valid_0's auc: 0.775133 [27] valid_0's auc: 0.776475 [28] valid_0's auc: 0.77654 [29] valid_0's auc: 0.777402 [30] valid_0's auc: 0.777487 [31] valid_0's auc: 0.777462 [32] valid_0's auc: 0.777524 [33] valid_0's auc: 0.778062 [34] valid_0's auc: 0.777742 [35] valid_0's auc: 0.778348 [36] valid_0's auc: 0.778726 [37] valid_0's auc: 0.779238 [38] valid_0's auc: 0.779449 [39] valid_0's auc: 0.780067 [40] valid_0's auc: 0.779956 [41] valid_0's auc: 0.780362 [42] valid_0's auc: 0.780415 [43] valid_0's auc: 0.780669 [44] valid_0's auc: 0.780786 [45] valid_0's auc: 0.781149 [46] valid_0's auc: 0.781231 [47] valid_0's auc: 0.781386 [48] valid_0's auc: 0.781814 [49] valid_0's auc: 0.78183 [50] valid_0's auc: 0.781902 [51] valid_0's auc: 0.782061 [52] valid_0's auc: 0.782548 [53] valid_0's auc: 0.782615 [54] valid_0's auc: 0.783205 [55] valid_0's auc: 0.784022 [56] valid_0's auc: 0.784129 [57] valid_0's auc: 0.784167 [58] valid_0's auc: 0.784331 [59] valid_0's auc: 0.78442 [60] valid_0's auc: 0.784602 [61] valid_0's auc: 0.784749 [62] valid_0's auc: 0.784838 [63] valid_0's auc: 0.785104 [64] valid_0's auc: 0.785134 [65] valid_0's auc: 0.785544 [66] valid_0's auc: 0.785553 [67] valid_0's auc: 0.785657 [68] valid_0's auc: 0.785782 [69] valid_0's auc: 0.786255 [70] valid_0's auc: 0.786491 [71] valid_0's auc: 0.78674 [72] valid_0's auc: 0.786871 [73] valid_0's auc: 0.786958 [74] valid_0's auc: 0.787156 [75] valid_0's auc: 0.787279 [76] valid_0's auc: 0.78741 [77] valid_0's auc: 0.787547 [78] valid_0's auc: 0.787625 [79] valid_0's auc: 0.787682 [80] valid_0's auc: 0.787975 [81] valid_0's auc: 0.788156 [82] valid_0's auc: 0.788366 [83] valid_0's auc: 0.788578 [84] valid_0's auc: 0.788651 [85] valid_0's auc: 0.788787 [86] valid_0's auc: 0.789026 [87] valid_0's auc: 0.789063 [88] valid_0's auc: 0.789263 [89] valid_0's auc: 0.789417 [90] valid_0's auc: 0.789467 [91] valid_0's auc: 0.789676 [92] valid_0's auc: 0.789727 [93] valid_0's auc: 0.7899 [94] valid_0's auc: 0.790139 [95] valid_0's auc: 0.790146 [96] valid_0's auc: 0.790475 [97] valid_0's auc: 0.790767 [98] valid_0's auc: 0.790938 [99] valid_0's auc: 0.791177 [100] valid_0's auc: 0.791463 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.791463 [1] valid_0's auc: 0.757698 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.757948 [3] valid_0's auc: 0.758047 [4] valid_0's auc: 0.758753 [5] valid_0's auc: 0.761685 [6] valid_0's auc: 0.761875 [7] valid_0's auc: 0.761995 [8] valid_0's auc: 0.762136 [9] valid_0's auc: 0.762108 [10] valid_0's auc: 0.761805 [11] valid_0's auc: 0.762741 [12] valid_0's auc: 0.763883 [13] valid_0's auc: 0.764031 [14] valid_0's auc: 0.764196 [15] valid_0's auc: 0.764499 [16] valid_0's auc: 0.764659 [17] valid_0's auc: 0.764847 [18] valid_0's auc: 0.76478 [19] valid_0's auc: 0.770272 [20] valid_0's auc: 0.77068 [21] valid_0's auc: 0.771017 [22] valid_0's auc: 0.771228 [23] valid_0's auc: 0.771304 [24] valid_0's auc: 0.772486 [25] valid_0's auc: 0.772417 [26] valid_0's auc: 0.772656 [27] valid_0's auc: 0.773035 [28] valid_0's auc: 0.773496 [29] valid_0's auc: 0.773718 [30] valid_0's auc: 0.773737 [31] valid_0's auc: 0.774286 [32] valid_0's auc: 0.774156 [33] valid_0's auc: 0.774419 [34] valid_0's auc: 0.775035 [35] valid_0's auc: 0.775044 [36] valid_0's auc: 0.775165 [37] valid_0's auc: 0.776456 [38] valid_0's auc: 0.776438 [39] valid_0's auc: 0.777963 [40] valid_0's auc: 0.77818 [41] valid_0's auc: 0.778965 [42] valid_0's auc: 0.779395 [43] valid_0's auc: 0.779625 [44] valid_0's auc: 0.779797 [45] valid_0's auc: 0.780017 [46] valid_0's auc: 0.78014 [47] valid_0's auc: 0.780392 [48] valid_0's auc: 0.780686 [49] valid_0's auc: 0.780941 [50] valid_0's auc: 0.781057 [51] valid_0's auc: 0.781848 [52] valid_0's auc: 0.781988 [53] valid_0's auc: 0.782345 [54] valid_0's auc: 0.782747 [55] valid_0's auc: 0.782932 [56] valid_0's auc: 0.783047 [57] valid_0's auc: 0.783231 [58] valid_0's auc: 0.78329 [59] valid_0's auc: 0.783585 [60] valid_0's auc: 0.783793 [61] valid_0's auc: 0.783722 [62] valid_0's auc: 0.783898 [63] valid_0's auc: 0.784182 [64] valid_0's auc: 0.784347 [65] valid_0's auc: 0.784653 [66] valid_0's auc: 0.784791 [67] valid_0's auc: 0.784979 [68] valid_0's auc: 0.785101 [69] valid_0's auc: 0.785438 [70] valid_0's auc: 0.785619 [71] valid_0's auc: 0.785697 [72] valid_0's auc: 0.785884 [73] valid_0's auc: 0.786129 [74] valid_0's auc: 0.786262 [75] valid_0's auc: 0.786407 [76] valid_0's auc: 0.78648 [77] valid_0's auc: 0.786622 [78] valid_0's auc: 0.786888 [79] valid_0's auc: 0.787043 [80] valid_0's auc: 0.787584 [81] valid_0's auc: 0.787626 [82] valid_0's auc: 0.787669 [83] valid_0's auc: 0.788003 [84] valid_0's auc: 0.788134 [85] valid_0's auc: 0.788419 [86] valid_0's auc: 0.788445 [87] valid_0's auc: 0.788551 [88] valid_0's auc: 0.78872 [89] valid_0's auc: 0.789029 [90] valid_0's auc: 0.789218 [91] valid_0's auc: 0.789434 [92] valid_0's auc: 0.789952 [93] valid_0's auc: 0.790057 [94] valid_0's auc: 0.79029 [95] valid_0's auc: 0.790682 [96] valid_0's auc: 0.791119 [97] valid_0's auc: 0.7913 [98] valid_0's auc: 0.791605 [99] valid_0's auc: 0.791886 [100] valid_0's auc: 0.792353 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.792353 [1] valid_0's auc: 0.760154 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.760161 [3] valid_0's auc: 0.761275 [4] valid_0's auc: 0.761194 [5] valid_0's auc: 0.761366 [6] valid_0's auc: 0.761239 [7] valid_0's auc: 0.764882 [8] valid_0's auc: 0.766496 [9] valid_0's auc: 0.766245 [10] valid_0's auc: 0.766683 [11] valid_0's auc: 0.767273 [12] valid_0's auc: 0.767175 [13] valid_0's auc: 0.767688 [14] valid_0's auc: 0.767789 [15] valid_0's auc: 0.768049 [16] valid_0's auc: 0.768333 [17] valid_0's auc: 0.768804 [18] valid_0's auc: 0.768959 [19] valid_0's auc: 0.76897 [20] valid_0's auc: 0.769512 [21] valid_0's auc: 0.769478 [22] valid_0's auc: 0.769664 [23] valid_0's auc: 0.769734 [24] valid_0's auc: 0.769994 [25] valid_0's auc: 0.770369 [26] valid_0's auc: 0.770508 [27] valid_0's auc: 0.770697 [28] valid_0's auc: 0.770724 [29] valid_0's auc: 0.771207 [30] valid_0's auc: 0.77529 [31] valid_0's auc: 0.775397 [32] valid_0's auc: 0.776178 [33] valid_0's auc: 0.776989 [34] valid_0's auc: 0.778373 [35] valid_0's auc: 0.778975 [36] valid_0's auc: 0.779451 [37] valid_0's auc: 0.779929 [38] valid_0's auc: 0.780117 [39] valid_0's auc: 0.780361 [40] valid_0's auc: 0.780526 [41] valid_0's auc: 0.780772 [42] valid_0's auc: 0.781169 [43] valid_0's auc: 0.781487 [44] valid_0's auc: 0.781734 [45] valid_0's auc: 0.781781 [46] valid_0's auc: 0.782008 [47] valid_0's auc: 0.782317 [48] valid_0's auc: 0.782598 [49] valid_0's auc: 0.782875 [50] valid_0's auc: 0.783112 [51] valid_0's auc: 0.783418 [52] valid_0's auc: 0.783485 [53] valid_0's auc: 0.783836 [54] valid_0's auc: 0.783857 [55] valid_0's auc: 0.783994 [56] valid_0's auc: 0.784202 [57] valid_0's auc: 0.784192 [58] valid_0's auc: 0.784464 [59] valid_0's auc: 0.785723 [60] valid_0's auc: 0.78571 [61] valid_0's auc: 0.78602 [62] valid_0's auc: 0.7861 [63] valid_0's auc: 0.786087 [64] valid_0's auc: 0.786222 [65] valid_0's auc: 0.786323 [66] valid_0's auc: 0.786404 [67] valid_0's auc: 0.786785 [68] valid_0's auc: 0.786823 [69] valid_0's auc: 0.787 [70] valid_0's auc: 0.787013 [71] valid_0's auc: 0.787273 [72] valid_0's auc: 0.787597 [73] valid_0's auc: 0.787749 [74] valid_0's auc: 0.788552 [75] valid_0's auc: 0.788607 [76] valid_0's auc: 0.788887 [77] valid_0's auc: 0.789096 [78] valid_0's auc: 0.789653 [79] valid_0's auc: 0.789639 [80] valid_0's auc: 0.789877 [81] valid_0's auc: 0.790263 [82] valid_0's auc: 0.790395 [83] valid_0's auc: 0.790688 [84] valid_0's auc: 0.790733 [85] valid_0's auc: 0.790967 [86] valid_0's auc: 0.791113 [87] valid_0's auc: 0.791254 [88] valid_0's auc: 0.79137 [89] valid_0's auc: 0.791645 [90] valid_0's auc: 0.79172 [91] valid_0's auc: 0.791966 [92] valid_0's auc: 0.792199 [93] valid_0's auc: 0.792516 [94] valid_0's auc: 0.792844 [95] valid_0's auc: 0.793063 [96] valid_0's auc: 0.793207 [97] valid_0's auc: 0.79347 [98] valid_0's auc: 0.79384 [99] valid_0's auc: 0.794088 [100] valid_0's auc: 0.794243 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.794243 [1] valid_0's auc: 0.759786 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.764657 [3] valid_0's auc: 0.765416 [4] valid_0's auc: 0.765122 [5] valid_0's auc: 0.768802 [6] valid_0's auc: 0.768371 [7] valid_0's auc: 0.768223 [8] valid_0's auc: 0.769696 [9] valid_0's auc: 0.770084 [10] valid_0's auc: 0.76985 [11] valid_0's auc: 0.770084 [12] valid_0's auc: 0.772553 [13] valid_0's auc: 0.772833 [14] valid_0's auc: 0.774962 [15] valid_0's auc: 0.776731 [16] valid_0's auc: 0.777085 [17] valid_0's auc: 0.778218 [18] valid_0's auc: 0.778599 [19] valid_0's auc: 0.779262 [20] valid_0's auc: 0.779785 [21] valid_0's auc: 0.780662 [22] valid_0's auc: 0.780817 [23] valid_0's auc: 0.781245 [24] valid_0's auc: 0.781309 [25] valid_0's auc: 0.78137 [26] valid_0's auc: 0.781547 [27] valid_0's auc: 0.781556 [28] valid_0's auc: 0.781683 [29] valid_0's auc: 0.781957 [30] valid_0's auc: 0.782143 [31] valid_0's auc: 0.78226 [32] valid_0's auc: 0.782258 [33] valid_0's auc: 0.782146 [34] valid_0's auc: 0.783026 [35] valid_0's auc: 0.782994 [36] valid_0's auc: 0.783926 [37] valid_0's auc: 0.783892 [38] valid_0's auc: 0.784254 [39] valid_0's auc: 0.78469 [40] valid_0's auc: 0.784658 [41] valid_0's auc: 0.784715 [42] valid_0's auc: 0.784692 [43] valid_0's auc: 0.785067 [44] valid_0's auc: 0.784851 [45] valid_0's auc: 0.78527 [46] valid_0's auc: 0.786097 [47] valid_0's auc: 0.786103 [48] valid_0's auc: 0.786391 [49] valid_0's auc: 0.786103 [50] valid_0's auc: 0.786322 [51] valid_0's auc: 0.786486 [52] valid_0's auc: 0.787117 [53] valid_0's auc: 0.787146 [54] valid_0's auc: 0.787302 [55] valid_0's auc: 0.787534 [56] valid_0's auc: 0.787693 [57] valid_0's auc: 0.787819 [58] valid_0's auc: 0.787985 [59] valid_0's auc: 0.788091 [60] valid_0's auc: 0.788141 [61] valid_0's auc: 0.788182 [62] valid_0's auc: 0.788354 [63] valid_0's auc: 0.788629 [64] valid_0's auc: 0.788776 [65] valid_0's auc: 0.788969 [66] valid_0's auc: 0.78913 [67] valid_0's auc: 0.789357 [68] valid_0's auc: 0.78942 [69] valid_0's auc: 0.789737 [70] valid_0's auc: 0.789753 [71] valid_0's auc: 0.790198 [72] valid_0's auc: 0.790309 [73] valid_0's auc: 0.790432 [74] valid_0's auc: 0.790811 [75] valid_0's auc: 0.791035 [76] valid_0's auc: 0.791106 [77] valid_0's auc: 0.791114 [78] valid_0's auc: 0.791274 [79] valid_0's auc: 0.791496 [80] valid_0's auc: 0.79162 [81] valid_0's auc: 0.791681 [82] valid_0's auc: 0.791771 [83] valid_0's auc: 0.791911 [84] valid_0's auc: 0.792032 [85] valid_0's auc: 0.792057 [86] valid_0's auc: 0.792311 [87] valid_0's auc: 0.792332 [88] valid_0's auc: 0.792474 [89] valid_0's auc: 0.792526 [90] valid_0's auc: 0.79275 [91] valid_0's auc: 0.792853 [92] valid_0's auc: 0.792966 [93] valid_0's auc: 0.793104 [94] valid_0's auc: 0.793066 [95] valid_0's auc: 0.79324 [96] valid_0's auc: 0.793248 [97] valid_0's auc: 0.793377 [98] valid_0's auc: 0.79337 [99] valid_0's auc: 0.793458 [100] valid_0's auc: 0.793566 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.793566 [1] valid_0's auc: 0.762215 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.772303 [3] valid_0's auc: 0.775269 [4] valid_0's auc: 0.774358 [5] valid_0's auc: 0.77402 [6] valid_0's auc: 0.77701 [7] valid_0's auc: 0.776882 [8] valid_0's auc: 0.775852 [9] valid_0's auc: 0.776006 [10] valid_0's auc: 0.778096 [11] valid_0's auc: 0.77758 [12] valid_0's auc: 0.776888 [13] valid_0's auc: 0.776609 [14] valid_0's auc: 0.776707 [15] valid_0's auc: 0.778561 [16] valid_0's auc: 0.777955 [17] valid_0's auc: 0.777753 [18] valid_0's auc: 0.778763 [19] valid_0's auc: 0.778335 [20] valid_0's auc: 0.778246 [21] valid_0's auc: 0.779333 [22] valid_0's auc: 0.779276 [23] valid_0's auc: 0.778949 [24] valid_0's auc: 0.780416 [25] valid_0's auc: 0.780641 [26] valid_0's auc: 0.780962 [27] valid_0's auc: 0.780591 [28] valid_0's auc: 0.781559 [29] valid_0's auc: 0.781823 [30] valid_0's auc: 0.781878 [31] valid_0's auc: 0.782692 [32] valid_0's auc: 0.782631 [33] valid_0's auc: 0.782614 [34] valid_0's auc: 0.783374 [35] valid_0's auc: 0.783385 [36] valid_0's auc: 0.783939 [37] valid_0's auc: 0.783825 [38] valid_0's auc: 0.783982 [39] valid_0's auc: 0.784469 [40] valid_0's auc: 0.786002 [41] valid_0's auc: 0.786036 [42] valid_0's auc: 0.786187 [43] valid_0's auc: 0.786532 [44] valid_0's auc: 0.787004 [45] valid_0's auc: 0.787682 [46] valid_0's auc: 0.787881 [47] valid_0's auc: 0.788149 [48] valid_0's auc: 0.788099 [49] valid_0's auc: 0.788289 [50] valid_0's auc: 0.788382 [51] valid_0's auc: 0.788686 [52] valid_0's auc: 0.788752 [53] valid_0's auc: 0.789079 [54] valid_0's auc: 0.789559 [55] valid_0's auc: 0.7896 [56] valid_0's auc: 0.789684 [57] valid_0's auc: 0.78988 [58] valid_0's auc: 0.789933 [59] valid_0's auc: 0.79029 [60] valid_0's auc: 0.790306 [61] valid_0's auc: 0.790442 [62] valid_0's auc: 0.790457 [63] valid_0's auc: 0.790812 [64] valid_0's auc: 0.791001 [65] valid_0's auc: 0.791055 [66] valid_0's auc: 0.791488 [67] valid_0's auc: 0.791523 [68] valid_0's auc: 0.791666 [69] valid_0's auc: 0.791733 [70] valid_0's auc: 0.791853 [71] valid_0's auc: 0.792079 [72] valid_0's auc: 0.792187 [73] valid_0's auc: 0.792463 [74] valid_0's auc: 0.792603 [75] valid_0's auc: 0.792743 [76] valid_0's auc: 0.792738 [77] valid_0's auc: 0.792841 [78] valid_0's auc: 0.792955 [79] valid_0's auc: 0.793102 [80] valid_0's auc: 0.793241 [81] valid_0's auc: 0.793332 [82] valid_0's auc: 0.793376 [83] valid_0's auc: 0.793485 [84] valid_0's auc: 0.793612 [85] valid_0's auc: 0.793715 [86] valid_0's auc: 0.793893 [87] valid_0's auc: 0.79398 [88] valid_0's auc: 0.794051 [89] valid_0's auc: 0.794168 [90] valid_0's auc: 0.794333 [91] valid_0's auc: 0.794413 [92] valid_0's auc: 0.794751 [93] valid_0's auc: 0.794833 [94] valid_0's auc: 0.794992 [95] valid_0's auc: 0.795076 [96] valid_0's auc: 0.795215 [97] valid_0's auc: 0.795345 [98] valid_0's auc: 0.79546 [99] valid_0's auc: 0.79568 [100] valid_0's auc: 0.795711 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.795711 [1] valid_0's auc: 0.760477 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.760477 [3] valid_0's auc: 0.761049 [4] valid_0's auc: 0.762803 [5] valid_0's auc: 0.764426 [6] valid_0's auc: 0.76481 [7] valid_0's auc: 0.764804 [8] valid_0's auc: 0.76486 [9] valid_0's auc: 0.765372 [10] valid_0's auc: 0.765314 [11] valid_0's auc: 0.766307 [12] valid_0's auc: 0.766468 [13] valid_0's auc: 0.766473 [14] valid_0's auc: 0.766878 [15] valid_0's auc: 0.767154 [16] valid_0's auc: 0.771358 [17] valid_0's auc: 0.771997 [18] valid_0's auc: 0.77235 [19] valid_0's auc: 0.773067 [20] valid_0's auc: 0.77316 [21] valid_0's auc: 0.773603 [22] valid_0's auc: 0.773982 [23] valid_0's auc: 0.77437 [24] valid_0's auc: 0.776197 [25] valid_0's auc: 0.776418 [26] valid_0's auc: 0.777278 [27] valid_0's auc: 0.777414 [28] valid_0's auc: 0.777641 [29] valid_0's auc: 0.778541 [30] valid_0's auc: 0.778702 [31] valid_0's auc: 0.778776 [32] valid_0's auc: 0.779424 [33] valid_0's auc: 0.781895 [34] valid_0's auc: 0.782156 [35] valid_0's auc: 0.782471 [36] valid_0's auc: 0.78238 [37] valid_0's auc: 0.782442 [38] valid_0's auc: 0.782723 [39] valid_0's auc: 0.783611 [40] valid_0's auc: 0.783936 [41] valid_0's auc: 0.784154 [42] valid_0's auc: 0.784687 [43] valid_0's auc: 0.784856 [44] valid_0's auc: 0.785017 [45] valid_0's auc: 0.785474 [46] valid_0's auc: 0.785745 [47] valid_0's auc: 0.786119 [48] valid_0's auc: 0.786212 [49] valid_0's auc: 0.78609 [50] valid_0's auc: 0.786079 [51] valid_0's auc: 0.786433 [52] valid_0's auc: 0.786534 [53] valid_0's auc: 0.78668 [54] valid_0's auc: 0.786942 [55] valid_0's auc: 0.787322 [56] valid_0's auc: 0.78739 [57] valid_0's auc: 0.787454 [58] valid_0's auc: 0.787588 [59] valid_0's auc: 0.787963 [60] valid_0's auc: 0.788005 [61] valid_0's auc: 0.788147 [62] valid_0's auc: 0.788331 [63] valid_0's auc: 0.788597 [64] valid_0's auc: 0.789037 [65] valid_0's auc: 0.789185 [66] valid_0's auc: 0.78975 [67] valid_0's auc: 0.789884 [68] valid_0's auc: 0.789872 [69] valid_0's auc: 0.790233 [70] valid_0's auc: 0.790472 [71] valid_0's auc: 0.790604 [72] valid_0's auc: 0.790855 [73] valid_0's auc: 0.790919 [74] valid_0's auc: 0.791129 [75] valid_0's auc: 0.79132 [76] valid_0's auc: 0.791519 [77] valid_0's auc: 0.791642 [78] valid_0's auc: 0.791805 [79] valid_0's auc: 0.791894 [80] valid_0's auc: 0.792156 [81] valid_0's auc: 0.79229 [82] valid_0's auc: 0.79234 [83] valid_0's auc: 0.792528 [84] valid_0's auc: 0.792846 [85] valid_0's auc: 0.792962 [86] valid_0's auc: 0.793151 [87] valid_0's auc: 0.793373 [88] valid_0's auc: 0.793494 [89] valid_0's auc: 0.793592 [90] valid_0's auc: 0.793746 [91] valid_0's auc: 0.793984 [92] valid_0's auc: 0.794137 [93] valid_0's auc: 0.794296 [94] valid_0's auc: 0.794592 [95] valid_0's auc: 0.794654 [96] valid_0's auc: 0.79484 [97] valid_0's auc: 0.795148 [98] valid_0's auc: 0.795326 [99] valid_0's auc: 0.795606 [100] valid_0's auc: 0.795675 Did not meet early stopping. Best iteration is: [100] valid_0's auc: 0.795675 [1] valid_0's auc: 0.7495 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.7495 [3] valid_0's auc: 0.7495 [4] valid_0's auc: 0.7495 [5] valid_0's auc: 0.7495 [6] valid_0's auc: 0.7495 [7] valid_0's auc: 0.7495 [8] valid_0's auc: 0.7495 [9] valid_0's auc: 0.7495 [10] valid_0's auc: 0.7495 [11] valid_0's auc: 0.7495 Early stopping, best iteration is: [1] valid_0's auc: 0.7495 [1] valid_0's auc: 0.748453 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.748453 [3] valid_0's auc: 0.748453 [4] valid_0's auc: 0.748453 [5] valid_0's auc: 0.748453 [6] valid_0's auc: 0.748453 [7] valid_0's auc: 0.748453 [8] valid_0's auc: 0.748453 [9] valid_0's auc: 0.748453 [10] valid_0's auc: 0.748453 [11] valid_0's auc: 0.748453 Early stopping, best iteration is: [1] valid_0's auc: 0.748453 [1] valid_0's auc: 0.748867 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.748867 [3] valid_0's auc: 0.748867 [4] valid_0's auc: 0.748867 [5] valid_0's auc: 0.748867 [6] valid_0's auc: 0.748867 [7] valid_0's auc: 0.748867 [8] valid_0's auc: 0.748867 [9] valid_0's auc: 0.748867 [10] valid_0's auc: 0.748867 [11] valid_0's auc: 0.748867 Early stopping, best iteration is: [1] valid_0's auc: 0.748867 [1] valid_0's auc: 0.748286 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.748286 [3] valid_0's auc: 0.748286 [4] valid_0's auc: 0.748286 [5] valid_0's auc: 0.748286 [6] valid_0's auc: 0.748286 [7] valid_0's auc: 0.748286 [8] valid_0's auc: 0.748286 [9] valid_0's auc: 0.748286 [10] valid_0's auc: 0.748286 [11] valid_0's auc: 0.748286 Early stopping, best iteration is: [1] valid_0's auc: 0.748286 [1] valid_0's auc: 0.757043 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.757043 [3] valid_0's auc: 0.757043 [4] valid_0's auc: 0.757043 [5] valid_0's auc: 0.757043 [6] valid_0's auc: 0.757043 [7] valid_0's auc: 0.757043 [8] valid_0's auc: 0.757043 [9] valid_0's auc: 0.757043 [10] valid_0's auc: 0.757043 [11] valid_0's auc: 0.757043 Early stopping, best iteration is: [1] valid_0's auc: 0.757043 [1] valid_0's auc: 0.752298 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.752298 [3] valid_0's auc: 0.752298 [4] valid_0's auc: 0.752298 [5] valid_0's auc: 0.752298 [6] valid_0's auc: 0.752298 [7] valid_0's auc: 0.752298 [8] valid_0's auc: 0.752298 [9] valid_0's auc: 0.752298 [10] valid_0's auc: 0.752298 [11] valid_0's auc: 0.752298 Early stopping, best iteration is: [1] valid_0's auc: 0.752298 [1] valid_0's auc: 0.754636 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.754636 [3] valid_0's auc: 0.754636 [4] valid_0's auc: 0.754636 [5] valid_0's auc: 0.754636 [6] valid_0's auc: 0.754636 [7] valid_0's auc: 0.754636 [8] valid_0's auc: 0.754636 [9] valid_0's auc: 0.754636 [10] valid_0's auc: 0.754636 [11] valid_0's auc: 0.754636 Early stopping, best iteration is: [1] valid_0's auc: 0.754636 [1] valid_0's auc: 0.757698 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.757698 [3] valid_0's auc: 0.757698 [4] valid_0's auc: 0.757698 [5] valid_0's auc: 0.757698 [6] valid_0's auc: 0.757698 [7] valid_0's auc: 0.757698 [8] valid_0's auc: 0.757698 [9] valid_0's auc: 0.757698 [10] valid_0's auc: 0.757698 [11] valid_0's auc: 0.757698 Early stopping, best iteration is: [1] valid_0's auc: 0.757698 [1] valid_0's auc: 0.760154 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.760154 [3] valid_0's auc: 0.760154 [4] valid_0's auc: 0.760154 [5] valid_0's auc: 0.760154 [6] valid_0's auc: 0.760154 [7] valid_0's auc: 0.760154 [8] valid_0's auc: 0.760154 [9] valid_0's auc: 0.760154 [10] valid_0's auc: 0.760154 [11] valid_0's auc: 0.760154 Early stopping, best iteration is: [1] valid_0's auc: 0.760154 [1] valid_0's auc: 0.759786 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.759786 [3] valid_0's auc: 0.759786 [4] valid_0's auc: 0.759786 [5] valid_0's auc: 0.759786 [6] valid_0's auc: 0.759786 [7] valid_0's auc: 0.759786 [8] valid_0's auc: 0.759786 [9] valid_0's auc: 0.759786 [10] valid_0's auc: 0.759786 [11] valid_0's auc: 0.759786 Early stopping, best iteration is: [1] valid_0's auc: 0.759786 [1] valid_0's auc: 0.762215 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.762215 [3] valid_0's auc: 0.762215 [4] valid_0's auc: 0.762215 [5] valid_0's auc: 0.762215 [6] valid_0's auc: 0.762215 [7] valid_0's auc: 0.762215 [8] valid_0's auc: 0.762215 [9] valid_0's auc: 0.762215 [10] valid_0's auc: 0.762215 [11] valid_0's auc: 0.762215 Early stopping, best iteration is: [1] valid_0's auc: 0.762215 [1] valid_0's auc: 0.760477 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.760477 [3] valid_0's auc: 0.760477 [4] valid_0's auc: 0.760477 [5] valid_0's auc: 0.760477 [6] valid_0's auc: 0.760477 [7] valid_0's auc: 0.760477 [8] valid_0's auc: 0.760477 [9] valid_0's auc: 0.760477 [10] valid_0's auc: 0.760477 [11] valid_0's auc: 0.760477 Early stopping, best iteration is: [1] valid_0's auc: 0.760477 [1] valid_0's auc: 0.7495 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.7495 [3] valid_0's auc: 0.7495 [4] valid_0's auc: 0.7495 [5] valid_0's auc: 0.7495 [6] valid_0's auc: 0.7495 [7] valid_0's auc: 0.7495 [8] valid_0's auc: 0.7495 [9] valid_0's auc: 0.7495 [10] valid_0's auc: 0.7495 [11] valid_0's auc: 0.7495 Early stopping, best iteration is: [1] valid_0's auc: 0.7495 [1] valid_0's auc: 0.748453 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.748453 [3] valid_0's auc: 0.748453 [4] valid_0's auc: 0.748453 [5] valid_0's auc: 0.748453 [6] valid_0's auc: 0.748453 [7] valid_0's auc: 0.748453 [8] valid_0's auc: 0.748453 [9] valid_0's auc: 0.748453 [10] valid_0's auc: 0.748453 [11] valid_0's auc: 0.748453 Early stopping, best iteration is: [1] valid_0's auc: 0.748453 [1] valid_0's auc: 0.748867 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.748867 [3] valid_0's auc: 0.748867 [4] valid_0's auc: 0.748867 [5] valid_0's auc: 0.748867 [6] valid_0's auc: 0.748867 [7] valid_0's auc: 0.748867 [8] valid_0's auc: 0.748867 [9] valid_0's auc: 0.748867 [10] valid_0's auc: 0.748867 [11] valid_0's auc: 0.748867 Early stopping, best iteration is: [1] valid_0's auc: 0.748867 [1] valid_0's auc: 0.748286 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.748286 [3] valid_0's auc: 0.748286 [4] valid_0's auc: 0.748286 [5] valid_0's auc: 0.748286 [6] valid_0's auc: 0.748286 [7] valid_0's auc: 0.748286 [8] valid_0's auc: 0.748286 [9] valid_0's auc: 0.748286 [10] valid_0's auc: 0.748286 [11] valid_0's auc: 0.748286 Early stopping, best iteration is: [1] valid_0's auc: 0.748286 [1] valid_0's auc: 0.757043 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.757043 [3] valid_0's auc: 0.757043 [4] valid_0's auc: 0.757043 [5] valid_0's auc: 0.757043 [6] valid_0's auc: 0.757043 [7] valid_0's auc: 0.757043 [8] valid_0's auc: 0.757043 [9] valid_0's auc: 0.757043 [10] valid_0's auc: 0.757043 [11] valid_0's auc: 0.757043 Early stopping, best iteration is: [1] valid_0's auc: 0.757043 [1] valid_0's auc: 0.752298 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.752298 [3] valid_0's auc: 0.752298 [4] valid_0's auc: 0.752298 [5] valid_0's auc: 0.752298 [6] valid_0's auc: 0.752298 [7] valid_0's auc: 0.752298 [8] valid_0's auc: 0.752298 [9] valid_0's auc: 0.752298 [10] valid_0's auc: 0.752298 [11] valid_0's auc: 0.752298 Early stopping, best iteration is: [1] valid_0's auc: 0.752298 [1] valid_0's auc: 0.754636 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.754636 [3] valid_0's auc: 0.754636 [4] valid_0's auc: 0.754636 [5] valid_0's auc: 0.754636 [6] valid_0's auc: 0.754636 [7] valid_0's auc: 0.754636 [8] valid_0's auc: 0.754636 [9] valid_0's auc: 0.754636 [10] valid_0's auc: 0.754636 [11] valid_0's auc: 0.754636 Early stopping, best iteration is: [1] valid_0's auc: 0.754636 [1] valid_0's auc: 0.757698 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.757698 [3] valid_0's auc: 0.757698 [4] valid_0's auc: 0.757698 [5] valid_0's auc: 0.757698 [6] valid_0's auc: 0.757698 [7] valid_0's auc: 0.757698 [8] valid_0's auc: 0.757698 [9] valid_0's auc: 0.757698 [10] valid_0's auc: 0.757698 [11] valid_0's auc: 0.757698 Early stopping, best iteration is: [1] valid_0's auc: 0.757698 [1] valid_0's auc: 0.760154 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.760154 [3] valid_0's auc: 0.760154 [4] valid_0's auc: 0.760154 [5] valid_0's auc: 0.760154 [6] valid_0's auc: 0.760154 [7] valid_0's auc: 0.760154 [8] valid_0's auc: 0.760154 [9] valid_0's auc: 0.760154 [10] valid_0's auc: 0.760154 [11] valid_0's auc: 0.760154 Early stopping, best iteration is: [1] valid_0's auc: 0.760154 [1] valid_0's auc: 0.759786 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.759786 [3] valid_0's auc: 0.759786 [4] valid_0's auc: 0.759786 [5] valid_0's auc: 0.759786 [6] valid_0's auc: 0.759786 [7] valid_0's auc: 0.759786 [8] valid_0's auc: 0.759786 [9] valid_0's auc: 0.759786 [10] valid_0's auc: 0.759786 [11] valid_0's auc: 0.759786 Early stopping, best iteration is: [1] valid_0's auc: 0.759786 [1] valid_0's auc: 0.762215 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.762215 [3] valid_0's auc: 0.762215 [4] valid_0's auc: 0.762215 [5] valid_0's auc: 0.762215 [6] valid_0's auc: 0.762215 [7] valid_0's auc: 0.762215 [8] valid_0's auc: 0.762215 [9] valid_0's auc: 0.762215 [10] valid_0's auc: 0.762215 [11] valid_0's auc: 0.762215 Early stopping, best iteration is: [1] valid_0's auc: 0.762215 [1] valid_0's auc: 0.760477 Training until validation scores don't improve for 10 rounds [2] valid_0's auc: 0.760477 [3] valid_0's auc: 0.760477 [4] valid_0's auc: 0.760477 [5] valid_0's auc: 0.760477 [6] valid_0's auc: 0.760477 [7] valid_0's auc: 0.760477 [8] valid_0's auc: 0.760477 [9] valid_0's auc: 0.760477 [10] valid_0's auc: 0.760477 [11] valid_0's auc: 0.760477 Early stopping, best iteration is: [1] valid_0's auc: 0.760477 [1] valid_0's auc: 0.762923 [2] valid_0's auc: 0.762923 [3] valid_0's auc: 0.762982 [4] valid_0's auc: 0.76328 [5] valid_0's auc: 0.76328 [6] valid_0's auc: 0.76338 [7] valid_0's auc: 0.76338 [8] valid_0's auc: 0.763386 [9] valid_0's auc: 0.76536 [10] valid_0's auc: 0.767171 [11] valid_0's auc: 0.767107 [12] valid_0's auc: 0.767159 [13] valid_0's auc: 0.772416 [14] valid_0's auc: 0.772331 [15] valid_0's auc: 0.77242 [16] valid_0's auc: 0.772598 [17] valid_0's auc: 0.773041 [18] valid_0's auc: 0.773071 [19] valid_0's auc: 0.772971 [20] valid_0's auc: 0.772972 [21] valid_0's auc: 0.772936 [22] valid_0's auc: 0.772894 [23] valid_0's auc: 0.772985 [24] valid_0's auc: 0.773115 [25] valid_0's auc: 0.773491 [26] valid_0's auc: 0.773984 [27] valid_0's auc: 0.775296 [28] valid_0's auc: 0.775961 [29] valid_0's auc: 0.776052 [30] valid_0's auc: 0.775913 [31] valid_0's auc: 0.776688 [32] valid_0's auc: 0.776406 [33] valid_0's auc: 0.776428 [34] valid_0's auc: 0.776256 [35] valid_0's auc: 0.776261 [36] valid_0's auc: 0.776724 [37] valid_0's auc: 0.776823 [38] valid_0's auc: 0.777754 [39] valid_0's auc: 0.777335 [40] valid_0's auc: 0.777309 [41] valid_0's auc: 0.777309 [42] valid_0's auc: 0.777453 [43] valid_0's auc: 0.778095 [44] valid_0's auc: 0.778059 [45] valid_0's auc: 0.777958 [46] valid_0's auc: 0.778428 [47] valid_0's auc: 0.77833 [48] valid_0's auc: 0.778252 [49] valid_0's auc: 0.778658 [50] valid_0's auc: 0.778503 [51] valid_0's auc: 0.779384 [52] valid_0's auc: 0.779283 [53] valid_0's auc: 0.779404 [54] valid_0's auc: 0.779851 [55] valid_0's auc: 0.779849 [56] valid_0's auc: 0.780255 [57] valid_0's auc: 0.780341 [58] valid_0's auc: 0.780195 [59] valid_0's auc: 0.780144 [60] valid_0's auc: 0.779917 [61] valid_0's auc: 0.779942 [62] valid_0's auc: 0.780441 [63] valid_0's auc: 0.780375 [64] valid_0's auc: 0.780362 [65] valid_0's auc: 0.781032 [66] valid_0's auc: 0.780952 [67] valid_0's auc: 0.780989 [68] valid_0's auc: 0.781004 [69] valid_0's auc: 0.781033 [70] valid_0's auc: 0.781128 [71] valid_0's auc: 0.781141 [72] valid_0's auc: 0.780912 [73] valid_0's auc: 0.780887 [74] valid_0's auc: 0.780896 [75] valid_0's auc: 0.780868 [76] valid_0's auc: 0.780729 [77] valid_0's auc: 0.78114 [78] valid_0's auc: 0.781278 [79] valid_0's auc: 0.781385 [80] valid_0's auc: 0.781349 [81] valid_0's auc: 0.781434 [82] valid_0's auc: 0.781471 [83] valid_0's auc: 0.781478 [84] valid_0's auc: 0.781458 [85] valid_0's auc: 0.782029 [86] valid_0's auc: 0.781957 [87] valid_0's auc: 0.781963 [88] valid_0's auc: 0.781996 [89] valid_0's auc: 0.781997 [90] valid_0's auc: 0.781915 [91] valid_0's auc: 0.781959 [92] valid_0's auc: 0.781939 [93] valid_0's auc: 0.782183 [94] valid_0's auc: 0.782168 [95] valid_0's auc: 0.782084 [96] valid_0's auc: 0.782157 [97] valid_0's auc: 0.782213 [98] valid_0's auc: 0.78221 [99] valid_0's auc: 0.782194 [100] valid_0's auc: 0.782236
GridSearchCV(cv=4, error_score=nan,
estimator=LGBMClassifier(boosting_type='gbdt', class_weight=None,
colsample_bytree=1.0,
importance_type='split',
learning_rate=0.1, max_depth=-1,
metric='auc', min_child_samples=20,
min_child_weight=0.001,
min_split_gain=0.0, n_estimators=100,
n_jobs=-1, num_iterations=100,
num_leaves=31, objective='binary',
random_state=None, reg...ha=0.0,
reg_lambda=0.0, silent=True,
subsample=1.0, subsample_for_bin=200000,
subsample_freq=0),
iid='deprecated', n_jobs=None,
param_grid={'boosting_type': ['dart', 'gbdt'],
'learning_rate': [0.005, 0.01, 0.0001],
'n_estimators': [3, 5], 'num_leaves': [12, 16, 20],
'random_state': [501]},
pre_dispatch='2*n_jobs', refit=True, return_train_score=False,
scoring=None, verbose=0)
lgb_grid_mdl.best_params_
{'boosting_type': 'dart',
'learning_rate': 0.01,
'n_estimators': 3,
'num_leaves': 20,
'random_state': 501}
train_probs_lgb = lgb_grid_mdl.predict_proba(x_train_rf)
test_probs_lgb = lgb_grid_mdl.predict_proba(x_test)
train_probs_df_lgb = pd.DataFrame(train_probs_lgb)
test_probs_df_lgb = pd.DataFrame(test_probs_lgb)
train_probs_df_lgb.columns = ['trainprobs' + str(col) for col in train_probs_df_lgb.columns]
test_probs_df_lgb.columns = ['testprobs' + str(col) for col in test_probs_df_lgb.columns]
fpr, tpr, thresholds = metrics.roc_curve(y_train_rf, train_probs_lgb[:,1])
metrics.auc(fpr, tpr)
0.7924184238583627
fpr, tpr, thresholds = metrics.roc_curve(y_test, test_probs_lgb[:,1])
metrics.auc(fpr, tpr)
0.78052522159409
# Reading in test data file
lab_test_df = pd.read_csv('PYTHON_LAB_DF_TEST_2.csv', sep = ",")
python_lab_test_df = lab_test_df.copy()
# Label Encoding
le = preprocessing.LabelEncoder()
le.fit(python_lab_test_df['SCHED_SURG_AREA'])
python_lab_test_df['SCHED_SURG_AREA'] = le.transform(python_lab_test_df['SCHED_SURG_AREA'])
python_lab_test_df['RACE'] = le.fit_transform(python_lab_test_df['RACE'].apply(str))
python_lab_test_df['ETHNIC_GROUP'] = le.fit_transform(python_lab_test_df['ETHNIC_GROUP'].apply(str))
python_lab_test_df['SCHED_HOSPITAL'] = le.fit_transform(python_lab_test_df['SCHED_HOSPITAL'].apply(str))
python_lab_test_df['SCHED_SURG_PROC_CD'] = le.fit_transform(python_lab_test_df['SCHED_SURG_PROC_CD'].apply(str))
python_lab_test_df['FEMALE'] = le.fit_transform(python_lab_test_df['FEMALE'].apply(str))
python_lab_test_df['CAV_REC_SEX'] = le.fit_transform(python_lab_test_df['CAV_REC_SEX'].apply(str))
python_lab_test_df['CAV_REC_LANG'] = le.fit_transform(python_lab_test_df['CAV_REC_LANG'].apply(str))
python_lab_test_df['CAV_REC_IPOP'] = le.fit_transform(python_lab_test_df['CAV_REC_IPOP'].apply(str))
python_lab_test_df['CAV_REC_PRIORITY_CODE'] = le.fit_transform(python_lab_test_df['CAV_REC_PRIORITY_CODE'].apply(str))
python_lab_test_df['CAV_REC_DISP_CODE'] = le.fit_transform(python_lab_test_df['CAV_REC_DISP_CODE'].apply(str))
python_lab_test_df = python_lab_test_df.drop(columns = ['PROC_DATE', 'CREATE_DT_TM', 'SCHED_START_DT_TM'])
predict_lab_test = gbm_rh.predict(python_lab_test_df.drop(columns = ['ID1']))
predict_lab_test
array([0.7274571 , 0.68008264, 0.79247017, ..., 0.74397117, 0.84123845,
0.38515668])
predict_lab_test_df = python_lab_test_df[['ID1']].copy()
predict_lab_test_df['LOS_PROB'] = predict_lab_test
predict_lab_test_df.head()
| ID1 | LOS_PROB | |
|---|---|---|
| 0 | 1 | 0.727457 |
| 1 | 2 | 0.680083 |
| 2 | 3 | 0.792470 |
| 3 | 4 | 0.180654 |
| 4 | 5 | 0.131683 |
# Deploying to a csv file.
predict_lab_test_df.to_csv("PYTHON_LAB_TEST_PROBABILITY.csv", sep=',', index=False)
# Importing SHAP and LIME
import shap
import lime
import lime.lime_tabular
gbm_features = list(x_train.columns)
print(gbm_features)
['SCHED_SURG_AREA', 'RACE', 'ETHNIC_GROUP', 'SCHED_HOSPITAL', 'SCHED_SURG_PROC_CD', 'FEMALE', 'AGE_ON_CONTACT_DATE', 'BMI', 'WEIGHT', 'BP_SYSTOLIC', 'BP_DIASTOLIC', 'PULSE', 'PCPVISIT', 'METFORMIN_FLAG', 'OPIOIDS_FLAG', 'ALPHA_BLOCKERS', 'CENTRAL_ANTAGONISTS', 'RENIN', 'BETA_BLOCKERS', 'ACE_INHIB', 'ARB', 'ALDOSTERONE_BLOCKERS', 'VASODIALATORS', 'DIURETICS', 'CALCIUM_BLOCKERS', 'STATINS', 'INSULIN_MEDS', 'ASPIRIN', 'WARFARIN', 'DOACS', 'PRETERM_17P', 'MEDROL', 'PREDNISONE', 'INHALED_STEROID_WITH_LABA', 'INHALED_STEROID_WITHOUT_LABA', 'INHALED_STEROIDS', 'ASTHMA_BIOLOGICS', 'SHORT_ACTING_BRONCHO_DIALATORS', 'TNF_INHIBITORS', 'IMMUNOMODULATORS', 'AMINOSALICYLATES', 'CORTICOSTEROIDS', 'ARNI', 'ALLOPURINOL', 'SEIZURE', 'MUSCLERELAXANT', 'DIGOXIN', 'INOTROPES', 'ANTI_ARRHYTHMIC', 'ANTIPLATELET', 'SULFONYLUREA', 'GLP_1_AGONIST', 'THIAZOLIDINEDIONE', 'SGLT2_INHIBITOR', 'DPP4_INHIBITOR', 'ALPHA_GLUCOSIDASE_INHIBITOR', 'AMYLINOMIMETIC', 'RAPID_ACTING_INSULIN', 'SHORT_ACTING_INSULIN', 'INTERMEDIATE_ACTING_INSULIN', 'LONG_ACTING_INSULIN', 'MINOCYCLINE', 'DOXYCYCLINE', 'MELATONIN', 'METHAZOLAMIDE', 'HYDROXYCHLOROQUINE', 'ITTC', 'DMARDS', 'OBESE_HST', 'MORBIDOBESE_HST', 'PH_HST', 'AFIB_HST', 'COPD_HST', 'CHF_HST', 'DIAB_HST', 'CAD_HST', 'OSTEO_HST', 'HTN_HST', 'CANCER_HST', 'LUNG_CANCER_HST', 'OVARIAN_CANCER_HST', 'HEAD_NECK_CANCER_HST', 'BREAST_CANCER_HST', 'ASTHMA_HST', 'GERD_HST', 'FIBROMYALGIA_HST', 'DEPRESSION_HST', 'PSORIATIC_ARTHRITIS_HST', 'RHEUM_ARTHRITIS_HST', 'LUPUS_HST', 'VTVF_HST', 'STROKE_HST', 'VASCULARDISEASE_HST', 'LOWBACKPAIN_HST', 'DVT_HST', 'PE_HST', 'HYPOTHYROIDISM_HST', 'ADRENAL_INSUFFICIENCY_HST', 'INFERTILITY_HST', 'CKD_HST', 'ESRD_HST', 'OBS_SLEEPAPNEA_HST', 'CARDIAC_ARREST_HST', 'HEMO_STROKE_HST', 'MAJOR_BLEED_HST', 'MACULAR_DEGEN_HST', 'ANXIETY_HST', 'HYPERLIPIDEMIA_HST', 'HIV_HST', 'ALZHEIMER_HST', 'COLORECTAL_CANCER_HST', 'ENDOMETRIAL_CANCER_HST', 'GLAUCOMA_HST', 'HIP_PELVIC_FRACTURE_HST', 'BENIGN_PROSTATIC_HYPERPLASIA_HST', 'CIRRHOSIS_HST', 'CIRRHOSIS_HST_1', 'CHOLESTEROL_CLOSEST', 'HDL_CLOSEST', 'LDL_CLOSEST', 'TRIG_CLOSEST', 'WBC_CLOSEST', 'HGB_CLOSEST', 'URIC_ACID_CLOSEST', 'HCO3_CLOSEST', 'SODIUM_CLOSEST', 'CREATININE_CLOSEST', 'EF_CLOSEST', 'FEV1_CLOSEST', 'EOS_CLOSEST', 'NEUTRO_CLOSEST', 'MONO_CLOSEST', 'BASOPHIL_CLOSEST', 'K_CLOSEST', 'EGFR_CLOSEST', 'TSH_CLOSEST', 'T4_CLOSEST', 'GLUCOSE_CLOSEST', 'HBA1C_CLOSEST', 'ESR_CLOSEST', 'VITAMIN_D_CLOSEST', 'MAGNESIUM_CLOSEST', 'FOLICAC_CLOSEST', 'VIT_B12_CLOSEST', 'BNP_CLOSEST', 'PLATELET_CLOSEST', 'PA_PRESSURE_CLOSEST', 'HEMATOCRIT_CLOSEST', 'ALBUMIN_CLOSEST', 'PREALBUMIN_CLOSEST', 'MR_CLOSEST', 'TR_CLOSEST', 'MEANPLATELETVOL_CLOSEST', 'MCH_CLOSEST', 'RDW_CLOSEST', 'MCV_CLOSEST', 'MCHC_CLOSEST', 'RBC_CLOSEST', 'LYMPHOCYTE_CLOSEST', 'CA125_CLOSEST', 'BILIRUBIN_CLOSEST', 'ALT_CLOSEST', 'AST_CLOSEST', 'CA_CLOSEST', 'PHOSPHORUS_CLOSEST', 'URINEPROTEIN_CLOSEST', 'TOTALPREVIOUSHOSPVISITS', 'TOTALPREVIOUSEDVISITS', 'TOTALPREVIOUSPCPVISITS', 'PREVIOUSSPECIALTYVISIT', 'PREVIOUSURGENTCAREVISIT', 'CAV_REC_SEX', 'CAV_REC_LANG', 'CAV_REC_AGE', 'CAV_REC_IPOP', 'CAV_REC_PRIORITY_CODE', 'CAV_REC_DISP_CODE', 'UREA_NITROGEN_MAX_1', 'UREA_NITROGEN_MIN_1', 'CALCIUM_MAX_1', 'CALCIUM_MIN_1', 'IRON_MAX_1', 'IRON_MIN_1', 'GLUCOSE_MAX_1', 'GLUCOSE_MIN_1', 'HGB_MAX_1', 'HGB_MIN_1', 'HEMATOCRIT_MAX_1', 'HEMATOCRIT_MIN_1', 'CHLORIDE_MAX_1', 'CHLORIDE_MIN_1', 'SODIUM_MAX_1', 'SODIUM_MIN_1', 'CREATININE_MAX_1', 'CREATININE_MIN_1', 'CARBON_DIOXIDE_MAX_1', 'CARBON_DIOXIDE_MIN_1', 'RBC_MAX_1', 'RBC_MIN_1', 'MCV_MAX_1', 'MCV_MIN_1', 'MCH_MAX_1', 'MCH_MIN_1', 'MCHC_MAX_1', 'MCHC_MIN_1', 'ANION_GAP_MAX_1', 'ANION_GAP_MIN_1', 'PLATELETS_MAX_1', 'PLATELETS_MIN_1', 'WBC_MAX_1', 'WBC_MIN_1', 'MEAN_PLATELET_VOLUME_MAX_1', 'MEAN_PLATELET_VOLUME_MIN_1', 'EGFR_MAX_1', 'EGFR_MIN_1', 'RDW_MAX_1', 'RDW_MIN_1', 'BASOPHILS_MAX_1', 'BASOPHILS_MIN_1', 'NEUTROPHILS_MAX_1', 'NEUTROPHILS_MIN_1', 'LYMPHOCYTES_MAX_1', 'LYMPHOCYTES_MIN_1', 'MONOCYTES_MAX_1', 'MONOCYTES_MIN_1', 'EOSINOPHILS_MAX_1', 'EOSINOPHILS_MIN_1', 'MAGNESIUM_MAX_1', 'MAGNESIUM_MIN_1', 'PHOSPHORUS_MAX_1', 'PHOSPHORUS_MIN_1', 'INR_MAX_1', 'INR_MIN_1', 'ALBUMIN_MAX_1', 'ALBUMIN_MIN_1', 'TOTAL_BILIRUBIN_MAX_1', 'TOTAL_BILIRUBIN_MIN_1', 'AST_MAX_1', 'AST_MIN_1', 'ALT_MAX_1', 'ALT_MIN_1', 'ALKALINE_PHOSPHATASE_MAX_1', 'ALKALINE_PHOSPHATASE_MIN_1', 'TOTAL_PROTEIN_MAX_1', 'TOTAL_PROTEIN_MIN_1', 'BUN_CREATININE_RATIO_MAX_1', 'ACTIVATED_PTT_MAX_1', 'BUN_CREATININE_RATIO_MIN_1', 'ACTIVATED_PTT_MIN_1', 'TROPONIN_I_MAX_1', 'TROPONIN_I_MIN_1', 'SPECIFIC_GRAVITY_URINE_MAX_1', 'SPECIFIC_GRAVITY_URINE_MIN_1', 'PROTEIN_URINE_MAX_1', 'PROTEIN_URINE_MIN_1', 'PH_URINE_MAX_1', 'PH_URINE_MIN_1', 'KETONES_URINE_MAX_1', 'KETONES_URINE_MIN_1', 'URINE_NITRITE_MAX_1', 'URINE_NITRITE_MIN_1', 'LEUKOCYTE_ESTERASE_MAX_1', 'LEUKOCYTE_ESTERASE_MIN_1', 'BLOOD_URINE_MAX_1', 'BLOOD_URINE_MIN_1', 'BILIRUBIN_URINE_MAX_1', 'BILIRUBIN_URINE_MIN_1', 'UROBILINOGEN_URINE_MAX_1', 'UROBILINOGEN_URINE_MIN_1', 'WHITE_BLOOD_CELLS_URINE_MAX_1', 'WHITE_BLOOD_CELLS_URINE_MIN_1', 'RED_BLOOD_CELLS_URINE_MAX_1', 'RED_BLOOD_CELLS_URINE_MIN_1', 'CALCULATED_OSMOLALITY_MAX_1', 'CALCULATED_OSMOLALITY_MIN_1', 'DIRECT_BILIRUBIN_MAX_1', 'DIRECT_BILIRUBIN_MIN_1', 'LACTATE_BLOOD_MAX_1', 'LACTATE_BLOOD_MIN_1', 'BACTERIA_MAX_1', 'BACTERIA_MIN_1', 'EPITHELIAL_CELLS_MAX_1', 'EPITHELIAL_CELLS_MIN_1', 'AG_RATIO_MAX_1', 'AG_RATIO_MIN_1', 'PCO2_ARTERIAL_MAX_1', 'PCO2_ARTERIAL_MIN_1', 'ADI_2015']
print(len(gbm_features))
288
# LIME does not take pandas dataframes as inputs. So, we must change the dataframe (x_train) to an array
gbm_exp_lime = lime.lime_tabular.LimeTabularExplainer(np.nan_to_num(x_train.values), feature_names = x_train.columns.values.tolist(),
mode = 'classification', discretize_continuous=False)
from lightgbm import LGBMClassifier
gbm_clf = lgb.LGBMClassifier(boosting_type = 'gbdt',
num_leaves = 201,
#max_depth = ,
learning_rate = 0.04
#n_estimators =
#,subsample_for_bin =
,objective = 'binary'
,metric = 'auc'
#,class_weight =
#,min_split_gain =
#,min_split_weight =
,min_child_weight = 700
#,min_child_samples =
,subsample = 0.65
#,subsample_freq =
#,colsample_bytree =
,reg_alpha = 73
,reg_lambda = 958
,importance_type = 'split' #will rank features by # of times it is used in model.'gain' for gain
,num_iterations = 1557
)
# LIME cannot handle NaN values
#gbm_exp_i = gbm_exp_lime.explain_instance(np.nan_to_num(x_test.values[100]), gbm_clf.predict_proba, num_features = 288)
“SHAP (SHapley Additive exPlanations) is used to explain the prediction of an instance x by computing the contribution of each feature to the prediction. The SHAP explanation method computes Shapley values from coalitional game theory. The feature values of a data instance act as players in a coalition. Shapley values tell us how to fairly distribute the “payout” (= the prediction) among the features.”
xgb_shap_explainer = shap.TreeExplainer(gbm_rh)
Setting feature_perturbation = "tree_path_dependent" because no background data was given.
xgb_shap_vals_train = xgb_shap_explainer.shap_values(x_train)
LightGBM binary classifier with TreeExplainer shap values output has changed to a list of ndarray
xgb_shap_vals_test = xgb_shap_explainer.shap_values(x_test)
# Variable importance summaries for SHAP - train data
shap.summary_plot(xgb_shap_vals_train, x_train)
# Variable importance summaries for SHAP - test data
shap.summary_plot(xgb_shap_vals_test, x_test)
xgb_shap_vals_train = np.array(xgb_shap_vals_train)
shap.initjs()
shap.force_plot(xgb_shap_explainer.expected_value[0], xgb_shap_vals_train[0][0,:], x_train.iloc[0,:])
xgb_shap_vals_train.shape
(2, 51200, 288)
import random
patient_number = 101
# patient_number = random.randint(0, xgb_shap_vals_train.shape[1]-1)
patient_number #101
101
shap.initjs()
shap.force_plot(xgb_shap_explainer.expected_value[0], xgb_shap_vals_train[0][patient_number,:], x_train.iloc[patient_number,:])
shap.initjs()
shap.force_plot(xgb_shap_explainer.expected_value[0], xgb_shap_vals_train[0][5010,:], x_train.iloc[5010,:])
shap.force_plot(xgb_shap_explainer.expected_value[1], xgb_shap_vals_train[1][:500,:], x_train.iloc[:500,:])
shap.dependence_plot("SCHED_SURG_PROC_CD", xgb_shap_vals_train[1], x_train, display_features=x_train)
shap.dependence_plot("SCHED_SURG_PROC_CD", xgb_shap_vals_train[0], x_train, display_features=x_train)
LightGBM is out best model.
We have re-tuned this model using hyperband. Also, we have retrained the model with the best parameters.
After retraining and retuning,
AUC on training: 0.967
AUC on testing: 0.839
Hence, there is a huge overfit.
We have trained the model using hyperopt also.
For this, Train AUC: 0.990758 and Test AUC: 0.830068
Here, the overfitting even greater than what we have got using hyperband.
We have tarined the model using GridSearch as well.
Here, Train AUC: 0.7924184238583627 and Test AUC: 0.78052522159409.
The model seems to be fit-fine here (as the Train-Test AUC difference is within 0.03). However, we get more accuracy when the hyperparameters are chosen manually.
Hence, we choose the model (which is fit-fine) when the hyperparameters are tuned manually.
LightGBM is our best model.
The variable importance for LightGBM has already been found out using SHAP.
Variable importance summaries for SHAP have also been plotted above(on both training and testing data).
The most important variables are:
As can be seen in the force plot, SCHED_SURG_PROC_CD put higher chance of LOS. For both Patient 0 and Patient 101. Though Patient 0 has less chance of LOS > 5, but Patient 101 has very high predicted risk of 1.98. For Patient 101 the risk increased by the decrement of SCHED_SURG_PROC_CD, as it is almost half of what Patient 0 has. So, it can be seen LOS risk is inversely proportional to SCHED_SURG_PROC_CD. It can be seen that for Patient 5010 SCHED_SURG_PROC_CD infact in the lower risk side of the explainer.